The processes of anaerobic digestion and co-digestion are complicated and the development of computational models that are capable of simulation and prediction of anaerobic digester performances can assist in the operation of the anaerobic digestion processes and the optimization for methane production. The artificial neural network approach is considered to be an appropriate and uncomplicated modelling approach for anaerobic digestion applications. This study developed neural network models to predict the outcomes of anaerobic co-digestion of leachate with pineapple peel using experimental data. The multilayered feed forward neural network model proposed was capable of predicting the outcomes of biogas production from the anaerobic co-digestion processes with a mean squared error for validation of 2.67 x 10-2 and a R value for validation of 0.9942. The approach was found to be effective, flexible and versatile in coping with the non-linear relationships using available information.