Key Takeaways
- U.S. disaster restoration services industry revenue reached $13.2 billion in 2023, up 5.4% from 2022
- Global water damage restoration market size was valued at $28.5 billion in 2022
- Fire and smoke restoration segment generated $4.1 billion in U.S. revenue in 2023
- U.S. disaster restoration CAGR 2018-2023 was 5.9%
- Global market projected to reach $55.7 billion by 2030 at 7.1% CAGR
- Water restoration segment expected 6.8% CAGR through 2028
- Water damage restoration holds 38% market share in 2023
- Fire and smoke damage segment 22% of U.S. industry revenue 2023
- Mold remediation 15% share globally 2022
- U.S. restoration industry employment totaled 46,300 in 2023
- Average hourly wage for restoration technicians $24.50 in 2023 U.S.
- Total U.S. establishments 14,567 in disaster restoration 2023
- U.S. Southeast holds 28% of industry establishments 2023
- Florida disaster restoration revenue $2.1 billion 2023
- Texas storm restoration market $1.8 billion annually
The restoration industry is large and growing due to increasing natural disasters worldwide.
Employment & Operational Metrics
Employment & Operational Metrics Interpretation
Growth Rates & Projections
Growth Rates & Projections Interpretation
Market Segmentation
Market Segmentation Interpretation
Market Size & Revenue
Market Size & Revenue Interpretation
Regional Distribution
Regional Distribution 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.
Sophie Moreland. (2026, February 13). Disaster Restoration Services Industry Statistics. Gitnux. https://gitnux.org/disaster-restoration-services-industry-statistics
Sophie Moreland. "Disaster Restoration Services Industry Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/disaster-restoration-services-industry-statistics.
Sophie Moreland. 2026. "Disaster Restoration Services Industry Statistics." Gitnux. https://gitnux.org/disaster-restoration-services-industry-statistics.
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