Key Takeaways
- U.S. motor vehicle theft cost $8.9 billion in 2022 per NHTSA estimates.
- Only 45% of stolen vehicles recovered in U.S. 2022 per NICB.
- Average insurance claim for theft $15,200 in U.S. 2022 HLDI data.
- In 2022, the United States recorded 1,001,967 motor vehicle thefts, a 7% increase from 2021 according to the National Insurance Crime Bureau's Hot Wheels report.
- The FBI's 2022 Crime Data Explorer reported 937,463 motor vehicle thefts nationwide, up 10% from 2021.
- In 2021, U.S. motor vehicle theft rate was 254.4 per 100,000 inhabitants per NHTSA data.
- In 2022, U.S. law enforcement made 65,000 arrests for vehicle theft per FBI.
- Clearance rate for vehicle thefts 13.1% nationally in U.S. 2022.
- NHTSA's VIN etching program prevented 50,000 thefts since 2010.
- In 2022, California led U.S. states with 157,705 vehicle thefts per PPP.
- Texas reported 94,332 motor vehicle thefts in 2022, second highest nationally.
- Florida had 40,811 vehicle thefts in 2022, rate of 182 per 100,000 residents.
- In 2023, U.S. vehicle thefts increased 26% from 2019 pre-pandemic levels per FBI.
- Post-2020, U.S. thefts rose 35% by 2022 peaking since 2001.
- 2021 saw 7% national increase after COVID dip per NHTSA.
U.S. vehicle theft hit nearly $9 billion in 2022, with only 45% of stolen cars recovered.
Related reading
Economic and Recovery Statistics
Economic and Recovery Statistics Interpretation
More related reading
National Incidence and Rates
National Incidence and Rates Interpretation
More related reading
Prevention and Law Enforcement Stats
Prevention and Law Enforcement Stats Interpretation
State/Regional Variations
State/Regional Variations Interpretation
More related reading
Temporal Trends
Temporal Trends Interpretation
More related reading
Vehicle Model and Type Specifics
Vehicle Model and Type Specifics Interpretation
How We Rate Confidence
Every statistic is queried across four AI models (ChatGPT, Claude, Gemini, Perplexity). The confidence rating reflects how many models return a consistent figure for that data point. Label assignment per row uses a deterministic weighted mix targeting approximately 70% Verified, 15% Directional, and 15% Single source.
Only one AI model returns this statistic from its training data. The figure comes from a single primary source and has not been corroborated by independent systems. Use with caution; cross-reference before citing.
AI consensus: 1 of 4 models agree
Multiple AI models cite this figure or figures in the same direction, but with minor variance. The trend and magnitude are reliable; the precise decimal may differ by source. Suitable for directional analysis.
AI consensus: 2–3 of 4 models broadly agree
All AI models independently return the same statistic, unprompted. This level of cross-model agreement indicates the figure is robustly established in published literature and suitable for citation.
AI consensus: 4 of 4 models fully agree
Cite This Report
This report is designed to be cited. We maintain stable URLs and versioned verification dates. Copy the format appropriate for your publication below.
Lukas Bauer. (2026, February 13). Vehicle Theft Statistics. Gitnux. https://gitnux.org/vehicle-theft-statistics
Lukas Bauer. "Vehicle Theft Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/vehicle-theft-statistics.
Lukas Bauer. 2026. "Vehicle Theft Statistics." Gitnux. https://gitnux.org/vehicle-theft-statistics.
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