Date palm (Phoenix dactylifera L.) seeds, a waste product as a new, novel, and natural biosorbent, were used to remove Cu(II) ions from aqueous solutions by a batch sorption process. In this study first the comparison of a Multiple Linear Regression (MLR) and an Adaptive Neuro-Fuzzy Inference System (ANFIS) applied for modeling the sorption process is presented. Results were evaluated using Root Mean Squared Error (RMSE) and coefficient of determination (R-2) as performance parameters. The experimental and model outputs displayed acceptable result for MLR and ANFIS; testing RMSE values were 0.6725 and 0.1716, and R-2 values were 0.7594 and 0.9843, respectively. It was determined that Adaptive Neuro-Fuzzy Inference System (ANFIS) may be effectively used to predict the sorption of Cu(II) onto date palm seeds.