In 2023, California was the state with the most motor vehicle thefts, with 208,668 motor vehicle thefts. Texas had the second most motor vehicle thefts, at 115,013.

Car Theft State-by-State (With Makes and Models)

The Most Stolen Makes and Models by Number of Thefts

By Joe Boutros [source]

About this dataset

This dataset aims to explore the car theft climate in the US. It contains information on the top ten most stolen cars (make, model and year) by State, as well as the top 25 stolen model year cars and their corresponding number of thefts. This data was gathered by The National Insurance Crime Bureau which reports this data annually to provide an insight into car theft prevention strategies. Insight included is not only which vehicle might be at higher risk of being stolen in a given state but also what kind of models/makes can be found among many states or nationwide with highest frequency of being stolen. Analyzing this dataset could help answer questions like “What are the most frequently targeted makes/models?” or “Which states have seen an increase or decrease in car thefts?” - perhaps providing invaluable insight for consumers on how to best protect their vehicles from potential theft

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How to use the dataset

This dataset contains information about the car thefts that occured in the United States, organized by state and make/model of the vehicle stolen. You can use this dataset to uncover trends of car theft and investigate how different states differ when it comes to car theft patterns. Below are a few ways you can use this data:

• Explore Car Thefts by State: Use the columns State and # of Thefts to compare total thefts across all states, or specific states if you wish.

• Compare Stolen Vs Non-Stolen Cars by Make / Model: Use the columns Make/Model and Thefts to look at which make/model cars were most frequently stolen in 2015, as well as compare them with models that were not stolen at all.

• Uncover Hot Wheels for Each State: Look at columns Rank and Model Year for each state to determine which specific hot wheels vehicles experienced the most thefts during that year from each state.

  • Dive Deeper into Model Years : Utilize columns Veh model Yr and Thefts_Year to explore correlations between vehicle model years & total number of thefts per year for particular models or overall data set trends (e..g identifying increases in theft frequency)

Research Ideas

• Identifying consumer trends on automotive theft to create targeted educational materials to help drivers stay safe and protect against theft.
• Creating geographical heat maps of car theft that could be consulted by drivers when they are considering purchasing a new vehicle or relocating.
• Providing data-driven recommendations on the best types of vehicles and precautions that drivers should take if they live in an area with higher rates of car theft

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: Dataset copyright by authors - You are free to: - Share - copy and redistribute the material in any medium or format for any purpose, even commercially. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original. - Keep intact - all notices that refer to this license, including copyright notices.

Columns

File: 2015_State_Top10Report_wTotalThefts.csv | Column name | Description | |:---------------|:--------------------------------------------------------| | State | The state in which the car theft occurred. (String) | | Rank | The rank of the car theft in the state. (Integer) | | Make/Model | The make and model of the car that was stolen. (String) | | Model Year | The year of the car that was stolen. (Integer) | | Thefts | The number of thefts of the car in the state. (Integer) |

File: Top25-2015-Models-2015-thefts-for-release.csv | Column name | Description | |:-----------------|:-------------------------------------------------------------------| | Theft_Year | The year in which the theft occurred. (Integer) | | Veh Model Yr | The model year of the vehicle that was stolen. (Integer) | | **...

The Hyundai Elantra was the most frequently stolen passenger vehicle in the United States in 2023, with 48,445 thefts among all model years of this car. The second most stolen vehicle was the Hyundai Sonata, with 42,813 thefts in 2023.

Vehicle Thefts by State and Make/Model

Identifying Highest Risk Models and Locations

By Joe Boutros [source]

About this dataset

This dataset compiled by the National Insurance Crime Bureau (NICB) reveals the top ten most stolen cars in each state and across the country during the year 2015. Additionally, this dataset provides information on the top 25 stolen model year cars in 2015. It offers insights into theft trends through valuable data points such as vehicle, make and model, and thefts per state. This dataset can help you gain access to important data which will enable you to make informed decisions about car purchase, insurance rates or areas where extra precaution may be necessary when it comes to protecting your automobile investment

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How to use the dataset

This dataset provides an in-depth look at the vehicles that are most often stolen in the United States during 2015. It can be used to understand which models and makes of cars are most frequently targeted by thieves on a state-by-state basis.

The two files included in this dataset provide information about both the general trends for all U.S. states and more specific insights about the top 25 stolen 2015 model year cars.

The first file, 2015_State_Top10Report_wTotalThefts.csv, includes detailed information regarding each of the top ten most stolen vehicles per state. Each row contains data such as state and rank, make/model, thefts by number and year of thefts as well as vehicle model year (allowing users to track trends over time). It is important to note that rank specifies which car is most frequently stolen overall within a given state for all years combined (and not just within 2015), whereas thefts only indicate how many times a specific vehicle was reported stolen within that chosen state for the given year (as stated above). Additionally, # of Thefts reflects how many times each model has been reported stolen nationally regardless of individual location or date - it gives an indication to how widespread a particular car's theft rate is across America. All in all this file provides valuable information regarding individual type and make/model combinations across various states in American while being able to pinpoint exact numbers with regards to frequency of theft over time intervals This can help inform users on whether certain makes/models have risen or decreased in desirability among thieves thus impacting their decision making when purchasing or insuring their own cars..

The second file Top25-2015-Models-2015-thefts-for-release.csv offers detailed insight into exactly 25 car models which were reported as being amongst those with highest localised incidence factor when concerning theft reports coming out of various US states throughout 2015 – consequently it may also be called „most popular” list amongst criminal circles when referring specifically NATIONALLY occurring incidents within one given calendar year . The average user can utilize this data along similar means as before - reviewing „popularity” title conferred upon them either locally through investigation into variations between popular target choices between different areas but also compare those against national rates too . It has one slight difference however from previous entry – model years covered revert exclusively towards brand new releases , i,.e maybe user would want

Research Ideas

• Targeted Crime Prevention Programs: Governments, law enforcement, and insurers can use this dataset to target areas with the highest rate of car thefts and create crime prevention programs tailored to those locations.
• Vehicle Security Analysis & Upgrades: Auto manufacturers can use this data to analyze which models are being stolen the most in certain states and adjust security systems accordingly.
• Insurance Loss Modeling & Rates: Insurance providers can use this dataset to refine their loss models by creating actuarial tables based on model type and region, which would help them better define risk profiles for customers in different locations across the country

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: Dataset copyright by authors - You are free to: - Share - copy and redistribute the material in any medium or format for any purpose, even commercially. - Adapt - remix, transform, and build upon the material...

In 2020, Vermont was the state with the least number of motor vehicle thefts in the United States, with only 264 motor vehicle thefts. Maine had the second fewest motor vehicle thefts in that year, at 862.

In 2023, the nationwide rate of motor vehicle theft in the United States was 318.7 reported cases per 100,000 population. While this is an increase from the previous year, it is a significant decrease from the rate in 1990, which stood at 657.8 motor vehicle thefts per 100,000 of the population.

Stolen Vehicle Locate and Immobilize Market Outlook

According to our latest research, the global Stolen Vehicle Locate and Immobilize market size reached USD 8.7 billion in 2024, demonstrating robust growth driven by increasing vehicle theft incidents and technological advancements in vehicle security. The market is projected to expand at a CAGR of 12.1% from 2025 to 2033, reaching a forecasted value of USD 24.1 billion by 2033. The primary growth factor propelling this market is the heightened demand for advanced vehicle security systems, supported by regulatory mandates and rising consumer awareness regarding vehicle safety.

One of the most significant growth drivers for the Stolen Vehicle Locate and Immobilize market is the alarming rise in global vehicle theft rates. Urbanization, increased vehicle ownership, and the proliferation of sophisticated criminal networks have made vehicle theft a critical concern for both individuals and organizations. As a result, there is a surging demand for state-of-the-art security solutions that not only facilitate real-time location tracking but also enable remote immobilization of stolen vehicles. Insurance companies are increasingly incentivizing the adoption of these systems by offering reduced premiums, which further encourages vehicle owners to invest in advanced anti-theft technologies. Additionally, the integration of Internet of Things (IoT) and artificial intelligence (AI) into stolen vehicle recovery solutions is enhancing their effectiveness, making them more appealing to a broader user base.

Another prominent factor fueling market growth is the evolving regulatory landscape. Governments across the globe are implementing stringent regulations and safety norms mandating the installation of vehicle tracking and immobilization systems, especially in commercial and fleet vehicles. For instance, several countries in Europe and Asia Pacific have introduced policies requiring commercial vehicles to be equipped with GPS-based tracking devices. These regulatory initiatives are not only aimed at curbing vehicle theft but also at improving road safety and fleet management efficiency. As compliance becomes a necessity, original equipment manufacturers (OEMs) and aftermarket service providers are increasingly incorporating advanced locate and immobilize technologies into their offerings, thus expanding the market’s reach.

Technological advancements are also playing a pivotal role in shaping the Stolen Vehicle Locate and Immobilize market. The advent of GPS, GSM, and RFID-based solutions, coupled with seamless integration into connected car platforms, has revolutionized vehicle security. Modern systems offer enhanced features such as real-time location updates, geofencing, automated alerts, and remote immobilization via mobile applications. The proliferation of cloud-based services and robust data analytics further strengthens the value proposition of these solutions, enabling rapid and efficient recovery of stolen vehicles. Furthermore, the entry of new market players and continuous R&D investments are fostering innovation, resulting in more reliable, user-friendly, and cost-effective products that cater to diverse customer needs.

Regionally, North America dominates the Stolen Vehicle Locate and Immobilize market due to its high vehicle ownership rates, advanced technological infrastructure, and strong regulatory framework. However, Asia Pacific is emerging as the fastest-growing region, propelled by rapid urbanization, increasing disposable incomes, and escalating vehicle theft incidents. Europe also holds a significant market share, primarily driven by stringent safety regulations and a well-established automotive industry. Latin America and the Middle East & Africa are witnessing gradual adoption, supported by growing awareness and government initiatives to enhance vehicle security. Overall, the market's regional dynamics are characterized by varying adoption rates, regulatory environments, and consumer preferences, shaping the competitive landscape and growth trajectory.

In 2023, an estimated 1,067,522 reported motor vehicle theft cases occurred in the United States. This is an increase from the previous year, when there were an estimated 948,119 cases of motor vehicle theft nationwide.

Recently, the car robbery rate in Brazil has been decreasing. In 2024, approximately 102.2 out of every 100,000 automobiles were stolen in the country, which represents a decrease from an average of over 114 auto thefts per 100,000 vehicles recorded one year before. That year, São Paulo was the Brazilian state that had the highest number of car thefts and break-ins.

In 2023, a total of 5,439 white Americans were arrested for arson in the United States in comparison to 1,876 Americans who were Black or African American.