The ability to predict fuel consumption during fires is essential for a wide range of applications, including estimation of fire effects and fire emissions. This project identified predictors of fuel consumption for the dominant fuel bed components (litter (<0.6-cm diameter dead material) and live herbs) during 217 prescribed fires in native longleaf pine ( Pinus palustris Mill.) and old-field loblolly pine ( Pinus taeda L.) – shortleaf pine ( Pinus echinata Mill.) communities in the southeastern United States. Additionally, these data were used to validate the First Order Fire Effects Model (FOFEM) fuel consumption computer model using custom and default fuel loads. Regression models using empirical data suggested that litter and live herb fuel consumption can be predicted by prefire litter and live herb fuel loads, litter and live herb fuel moisture, litter fuel bed bulk density, season of burn, years since fire, days since last rain ≥0.64 cm, relative humidity, energy release component, community type, pine and hardwood basal areas, and the Keetch–Byram drought index. FOFEM’s prediction of fuel consumption for litter, live herbs, and duff combined using default fuel loads was 1.5 times the measured fuel consumption (where duff fuel load was zero). Refinement of FOFEM’s fuel load and consumption calculations in the studied community types using the newly collected data and suggestions for model improvement would provide more accurate air quality inventories and assist in guiding appropriate regulation of prescribed fire.