Pollarding of oak trees for livestock and animal feeding is a traditional application, and it has been used for centuries from generation to generation in southern and southeastern Turkey. Estimation of the fresh sprout biomass (FSB) potential of pollarded oak forests in high accuracy is important for sustainable forest management. In the present study, 40 trees were sampled from Turkey oak (Quercus cerris L.) stands that have been irregularly pollarded for animal husbandry in Adyaman, southeastern Turkey. In order to estimate FSB, a multiple logarithmic linear model was developed with explanatory variables such as tree diameter at breast height (DBH), total tree height (H), mean sprout length (SL), and mean sprout age (SA), which are in a significant relationship with FSB. Stepwise multiple regression analysis was used to fit this multiple logarithmic linear model and to determine the best independent variable set. As a result of stepwise regression analysis, three models were obtained in which SL, DBH, and SA are independent variables. Model 1 estimates the FSB by taking only SL, Model 2 uses SL and DBH, and Model 3 uses SL, DBH, and SA as independent variables. All models were significant at p=0.001 level. Model 1 explained the variation in FSB by 65%, Model 2 by 81%, and Model 3 by 86%. Inclusion of DBH in the model (Model 2) decreased the mean absolute error (MAE) of FSB by 26% and the inclusion of SA (Model 3) decreased MAE by 43%.