The Chaboche kinematic hardening model is generally used for modeling the plastic behaviour of material under quasi-static cyclic and monotonic loadings. This model is independent of strain rate and its constants are normally determined through quasi-static tests. Therefore, it cannot predict material behavior under high strain rate condition. On the other hand, the dynamic behaviour of materials even in some cyclic loadings is usually strain rate sensitive. In this investigation, the constants of Chaboche model are identified at various strain rates through quasi-static and dynamic tests and using these constants the effect of strain rate is incorporated in the Chaboche model. Moreover, the stress-strain diagrams at different strain rates are predicted using artificial neural network (ANN) and the results are compared with the experimental data. The results from the strain rate dependent Chaboche model shows reasonable agreement with the experimental data and the prediction from ANN. It is also shown in this work that the constants of Chaboche plasticity model are strain rate dependent and if the neural network is trained properly, it can be used for interpolating between the experimental data