McLain, MS
How exposed is McLain to wildfire?
McLain sits at the 86th percentile nationally for wildfire risk to structures — in USFS's highest wildfire-risk band nationally — per USFS's Wildfire Risk to Communities model, built from its 337 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, McLain's burn probability — fire likelihood with no building count factored in — sits at the 88th percentile nationally.
What "at risk" means for the buildings here
337 buildings are counted in McLain, and 80.4% of them sit in USFS's Direct exposure zone — flame contact, not just ember cast, is the live possibility for most of them, against 0% rated Minimal.
Where McLain ranks
There's little gap between McLain's 86th national percentile and its 89th percentile inside Mississippi, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, McLain ranks 4,441 for wildfire risk (1 is highest) and 20,660 by building count (1 is largest). Within Mississippi alone, it ranks 47 of 420 places by risk. See the full county-by-county picture for Mississippi on its state page.
What this risk score means for insurance
McLain's 86th-percentile, very high rating is the kind of score behind a broader national pattern: insurers pulling back from the highest wildfire-risk markets, non-renewing or declining new policies outright, most visibly in California. Shopping around, not assuming automatic renewal, tends to matter here.
Hardening a home in McLain
McLain's 80.4% Direct-exposure share means lot clearing around the structure typically outweighs any single material upgrade here. The home-hardening guide ranks the options for a place shaped like this.
Where McLain's figures come from
The methodology guide shows exactly how USFS turned 337 counted buildings into the percentiles shown above for McLain. The exposure-zones guide covers what McLain's dominant direct exposure actually means, with real examples from across the dataset.