Bene hull antioxidant activity is mainly related to Polyphenolic compounds. The present study focused on modelling the amount of bene hull (Pistacia atlantica) polyphenolic compounds extracted with subcritical water method, using back propagation neural network. To develop model, experimental data obtained from conducted experiments, converted into neural network model and process input variables including temperature (110-200°C), process time(30-60 min) and solvent mixing ratio (1:10 - 1:50). Also, the amount of Polyphenolic contents (mg Gallic acid/kg) was considered as the main indicator of the process. In the next stage developed model was optimized using Enumeration method and in order to evaluate the correctitude of the predicted value by the proposed method, actual experiments was carried out based on the obtained optimal process parameters. This study illustrated that extraction with subcritical water can be used as an environmental friendly process and fast extraction method to obtain Polyphenolic compounds from Bene hull.

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