Present work involves detailed experimentation on pump-mixer, and processing of experimental data to model its head and power characteristics using multi-variable least square based empirical correlations and artificial neural network (ANN). The latter modelling technique is shown to be superior. Trained and frozen ANN model has been used to generate head and power characteristics. Wherever possible, these characteristics have been qualitatively compared with the observations reported earlier. Also, an attempt has been made to physically explain these characteristics in order to demonstrate that the ANN model successfully captures the physics of the system. (C) 2004 Elsevier Ltd. All rights reserved.