Proton Exchange Membrane Fuel Cell (PEMFC) is a promising renewable energy, while still limited by the short life duration. To postpone the end of life, approaches of health management and prognostic (PHM) are applied into the cells. The stack voltage and impedance are often used as the health indicator (HI) for estimating state of health (SoH) and predicting remaining useful life (RUL). However, on one hand, on-line measurement of impedance is hardly realizable while downtime measure costs a lot. On the other hand, a single HI based on voltage or impedance is difficult to express the degradation of PEMFC precisely. To tackle this problem, this paper develops a fusion HI and a prognostic methodology for PEMFC SoH estimation and RUL prediction. Moreover, geodesic distance is employed to estimate SoH. Afterwards, a 2nd order Gaussian degradation model is built to complete the RUL prognostics based on unscented particle filter (UPF). In the experiment, both mahalanobis distance and geodesic distance are employed to estimate the SoH based on the presented HI. Besides, a rational model is applied to predict the RUL compared with the proposed Gaussian model. Finally, the results show the efficiency and effectiveness of the SoH estimation and RUL prediction approaches based on the proposed HI. (C) 2017 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.