WildfireRiskFinder

McMillin, WA

McMillin, WA's wildfire risk, in USFS's own numbers

Low
20thpercentile nationally

McMillin's 814 buildings earn a 20th-percentile wildfire-risk score nationally under USFS's model — among the lower wildfire-risk places nationally. (Source: USFS's Wildfire Risk to Communities methodology.)

USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts McMillin at the 21st percentile, close to its 20th-percentile risk score.

What "at risk" means for the buildings here

814Total buildings
11.8%Direct exposure
88.2%Indirect exposure
0%Minimal exposure

88.2% of McMillin's 814 buildings fall in USFS's Indirect exposure zone — ember cast rather than direct flame — against 11.8% Direct and 0% Minimal. Vent screens and roofing material matter more here than lot clearing alone.

Where McMillin ranks

McMillin's risk sits at a similar level relative to Washington (30th percentile statewide) as it does nationally (20th) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, McMillin ranks 25,322 for wildfire risk (1 is highest) and 13,516 by building count (1 is largest). Within Washington alone, it ranks 441 of 628 places by risk. See the full county-by-county picture for Washington on its state page.

McMillin and the insurance market

At the 20th national percentile, McMillin rates low for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.

What would actually reduce this score

With ember exposure the dominant pattern in McMillin (88.2% Indirect), vent screens and roofing material tend to matter more than lot clearing alone. The home-hardening guide covers both.

Where McMillin's figures come from

McMillin's 20th-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 McMillin's dominant indirect exposure actually means, with real examples from across the dataset.