Reliable pre-season predictions for wild turkey harvests can be an important component of management plans where hunter and/or harvest quotas are used. Data collected in Florida from 1983-1989 included 9 demographic and 4 meteorological variables. Using regression analyses we identified those variables which were associated with spring turkey harvest and produced a "best" regression model for making preseason, spring harvest predictions from data collected during the previous year. Variables identified as most important included: harvest, total number of turkeys observed in late summer surveys, and rainfall during the spring harvest season. The regression model employing these independent variables accounted for 94% of the variation in the following year's harvest. Collection of such data is feasible under state wildlife agency fiscal and manpower constraints. Their use gives biologists additional information upon which to base management decisions.