Plevna, MT
Plevna, MT's wildfire risk, in USFS's own numbers
Out of every US place USFS scores, Plevna lands at the 82nd percentile for wildfire risk to structures — in USFS's highest wildfire-risk band nationally — a figure built from its 184 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Plevna at the 82nd national percentile — 0 points above its risk-to-structures score, a gap driven by how much is actually built there.
What "at risk" means for the buildings here
Most of Plevna's buildings (71.7%) sit in the Indirect zone, where wind-blown embers rather than flame front are the mechanism USFS is scoring — ember-resistant vents and non-combustible roofing are the interventions this pattern favors, more than defensible space alone.
Where Plevna ranks
Plevna ranks lower within Montana (56th percentile statewide) than its 82nd national percentile suggests alone — a calmer spot in a state where wildfire risk generally runs high. Among the 31,521 US communities USFS scores, Plevna ranks 5,704 for wildfire risk (1 is highest) and 25,471 by building count (1 is largest). Within Montana alone, it ranks 210 of 475 places by risk. See the full county-by-county picture for Montana on its state page.
What this risk score means for insurance
Plevna's very high rating (82nd percentile) puts it among the places where the national carrier-pullback trend is most relevant — not a guarantee of a coverage problem, but a reason to shop rather than assume.
What would actually reduce this score
Because 71.7% of Plevna's buildings sit in the Indirect zone, sealing the ember pathway (vents, roofing, gutters) is the intervention this page's data actually supports — see the home-hardening guide.
Where Plevna's figures come from
Plevna's 82nd-percentile score and its burn-probability figure both come from the same USFS workbook, documented in the methodology guide. The exposure-zones guide covers what Plevna's dominant indirect exposure actually means, with real examples from across the dataset.