Annual recruitment of eastern wild turkeys (Meleagris gallopavo silvestris) should be closely monitored to regulate fall turkey seasons and reduce risk of over-harvest. However, previous studies have not encompassed the spatial or temporal scales needed to produce models that can consistently predict recruitment over a large region. Our objective was to assess the ability of using long-term data sets of sex-age ratios, oak (Quercus spp.) mast, and weather variables to forecast annual wild turkey recruitment in western Virginia. We conducted a thorough literature search on factors believed to be limiting reproduction and developed a series of 14 a priori models and 1 a posteriori model to predict recruitment. We used fall harvest ratios of juveniles per adult female, averaged over 26 western Virginia counties, during 1973-2002 as an index to annual recruitment and investigated the relationship of recruitment to age structure of the population, oak mast production in the previous fall, and spring weather. We considered impacts of different weather severity measures and investigated effects of deviation from mean, 90%, and 75% quartile values on recruitment. Our best model (w9 = 0.812) predicting recruitment incorporated May and June rainfall and March temperatures at the 75% quartile scale. This model accounted for a significant amount of variation in recruitment residuals (R2 = 0.50, R2adj = 0.44). Monitoring these selected weather parameters offers managers the ability to predict significant changes in recruitment annually.