Despite a growing need to expand the pace and scale of prescribed burning to address the national fire deficit, there is a lack of data-driven methods to incorporate fire danger information into prescribed fire planning. To address this gap, we combined nearly two decades of prescribed fire and wildfire records with spatial fire danger data across Montana and Idaho to characterize when and where each fire type has occurred. We identified objective thresholds from a normalized fire danger index, the Energy Release Component (ERC), by treating pile burns, broadcast burns, and wildfires as ordinal classes along an ERC continuum. We generated distributions of optimal thresholds to create “overlap zones” that quantify uncertainty between fire types. These methods were used to build a simple planning guide, ClassiFiRxe, that can help reveal fire class seasonality, estimate prescribed burn windows at local scales, and map categories across large landscapes. ClassiFiRxe can be developed wherever sufficient fire weather and occurrence data exist. This data-driven framework provides a repeatable, interpretable and robust tool to support prescribed fire planning, helping restore fire to landscapes and reduce the fire deficit.