The catalytic oxidation of ethyl acetate in low concentration was investigated over mono-metallic Ag/ZSM5 and bimetallic (Ni, Mn)-Ag/ZSM-5 catalysts. Catalytic studies were carried out in a catalytic fixed bed reactor under atmospheric pressure. The sequence of catalytic activity was as follows: Ni-Ag-ZSM-5 > Mn-Ag-ZSM-5 > Ag-ZSM-5 > H-ZSM-5. The catalysts were characterized by ICP-AES, X-ray diffraction (XRD), low temperature nitrogen adsorption, NH3-TPD, transmission electron microscopy (TEM), scanning electron microscopy (SEM) and diffuse reflectance UV–vis spectra (UV–vis). An artificial neural networks (ANN) model was developed to predict the performance of catalytic oxidation process over bimetallic Ni-Ag/ZSM-5 catalyst based on experimental data. For this purpose the standard feed forward back propagation algorithm was employed to train the model by using laboratory experimental data. A good agreement was resulted between experimental results and those obtained by ANN. Following order for variables effects on conversion yield of ethyl acetate was predicted by ANN model: reaction temperature (32.99%) > Ag loading (27.38%) > initial ethyl acetate concentration (23.58%) > Ni loading (16.05%).