This paper investigates the polymer electrolyte membrane (PEM) fuel cell internal behaviour variation at different operating condition, with characterization test data taken at predefined inspection times, and uses the determined internal behaviour evolution to predict the future PEM fuel cell performance. For this purpose, a PEM fuel cell behaviour model is used, which can be related to various fuel cell losses. By matching the model to the collected polarization curves from the PEM fuel cell system, the variation of fuel cell internal behaviour can be obtained through the determined model parameters. From the results, the source of PEM fuel cell degradation during its lifetime at different conditions can be better understood. Moreover, with determined fuel cell internal behaviour, the future fuel cell performance can be obtained by predicting the future model parameters. By comparing with prognostic results using adaptive neuro fuzzy inference system (ANFIS), the proposed prognostic analysis can provide better predictions for PEM fuel cell performance at dynamic condition, and with the understanding of variation in PEM fuel cell internal behaviour, mitigation strategies can be designed to extend the fuel cell performance. (C) 2017 The Author(s). Published by Elsevier B.V.