Abstract: Genetic Algorithm and Multiple Linear Regression (GA-MLR) and Levenberg-Marquardt Artificial Neural Network (L-M ANN) techniques were used to investigate the correlation between Trolox Equivalent Antioxidant Capacity (TEAC) and descriptors for 16 derivative hydroxy compounds. The applied internal validation method was used for the predictive power of four models. The square correlation coefficient between experimental and predicted TEAC for these data by GA-MLR and were 0.824 and 0.966, respectively. This is the first research on the QSAR of the antioxidant compounds against the TEAC using the L-M ANN.