Numerical simulations and decline curve analysis are classic tools used for predicting reservoir performance. Numerical simulations are a very complex tool, offering a nonunique solution with a high degree of uncertainty. Decline curve analysis does not take into account opening or closing intervals and variable injection rates. In this study, the authors designed a feedforward backpropagation neural network model as an alternative technique for predicting oil reservoir production performance. Real historical production data obtained from a Libyan oil field was used to train the network. This training network can serve as a practical reservoir production management tool.