Biltmore Forest, NC
How exposed is Biltmore Forest to wildfire?
Biltmore Forest sits at the 55th percentile nationally for wildfire risk to structures — modestly above the national average for wildfire risk — per USFS's Wildfire Risk to Communities model, built from its 743 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Biltmore Forest's burn probability — fire likelihood with no building count factored in — sits at the 58th percentile nationally.
Where Biltmore Forest's buildings actually sit
95.6% of Biltmore Forest's 743 buildings sit in USFS's Direct exposure zone, roughly 710 structures close enough to burnable vegetation for flame contact, not just embers — 4.4% fall in the Indirect, ember-only zone and 0% are Minimal.
Where Biltmore Forest ranks
Biltmore Forest's risk sits at a similar level relative to North Carolina (52nd percentile statewide) as it does nationally (55th) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Biltmore Forest ranks 14,125 for wildfire risk (1 is highest) and 14,198 by building count (1 is largest). Within North Carolina alone, it ranks 370 of 772 places by risk. See the full county-by-county picture for North Carolina on its state page.
Biltmore Forest and the insurance market
Biltmore Forest's elevated rating (55th percentile nationally) sits outside the range where wildfire risk alone reshapes an insurance market — still, a homeowner here loses nothing by comparing rates.
Lowering exposure, not just insuring around it
Because Direct exposure dominates in Biltmore Forest (95.6%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.
Where Biltmore Forest's figures come from
The methodology guide shows exactly how USFS turned 743 counted buildings into the percentiles shown above for Biltmore Forest. The exposure-zones guide covers what Biltmore Forest's dominant direct exposure actually means, with real examples from across the dataset.