Crellin, MD
Crellin, MD's wildfire risk, in USFS's own numbers
USFS's Wildfire Risk to Communities model puts Crellin at the 48th national percentile for risk to structures, modestly above the national average for wildfire risk — a score built from 144 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Crellin at the 48th percentile, close to its 48th-percentile risk score.
Crellin's building exposure, zone by zone
96.5% of Crellin's 144 buildings sit in USFS's Direct exposure zone, roughly 139 structures close enough to burnable vegetation for flame contact, not just embers — 3.5% fall in the Indirect, ember-only zone and 0% are Minimal.
Where Crellin ranks
Compare Crellin's two percentiles: 68th within Maryland, only 48th nationally — a gap of 19 points that marks it as unusually exposed for its own state. Among the 31,521 US communities USFS scores, Crellin ranks 16,325 for wildfire risk (1 is highest) and 27,123 by building count (1 is largest). Within Maryland alone, it ranks 172 of 527 places by risk. See the full county-by-county picture for Maryland on its state page.
Crellin and the insurance market
Crellin's elevated wildfire rating (48th percentile) isn't the kind of score driving the carrier pullback making news in the highest-risk Western markets — but a standard homeowners quote is still worth comparing on its own terms.
Lowering exposure, not just insuring around it
With 96.5% of Crellin in Direct exposure, defensible-space clearing and ember-resistant construction (vents, Class-A roofing) address the exposure this page's own numbers describe, not a generic checklist. See the home-hardening guide.
Where Crellin's figures come from
Crellin's 48th-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 Crellin's dominant direct exposure actually means, with real examples from across the dataset.