Hartford, KY
Hartford wildfire risk explained
Hartford sits at the 27th percentile nationally for wildfire risk to structures — close to the middle of USFS's national wildfire-risk range — per USFS's Wildfire Risk to Communities model, built from its 1,401 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Hartford at the 29th percentile, close to its 27th-percentile risk score.
What "at risk" means for the buildings here
1,401 buildings are counted in Hartford, and 54.3% of them sit in USFS's Direct exposure zone — flame contact, not just ember cast, is the live possibility for most of them, against 45% rated Minimal.
Hartford against the rest of the country
Hartford's 52nd-percentile standing inside Kentucky outpaces its 27th national percentile — this is a hotter spot than most of its own state, even though the state as a whole runs cooler nationally. Among the 31,521 US communities USFS scores, Hartford ranks 22,914 for wildfire risk (1 is highest) and 9,626 by building count (1 is largest). Within Kentucky alone, it ranks 268 of 552 places by risk. See the full county-by-county picture for Kentucky on its state page.
Shopping for coverage in Hartford
Hartford's moderate wildfire rating (27th 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
Hartford's 54.3% 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 Hartford's figures come from
The methodology guide shows exactly how USFS turned 1,401 counted buildings into the percentiles shown above for Hartford. The exposure-zones guide covers what Hartford's dominant direct exposure actually means, with real examples from across the dataset.