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Particle filter has been developing prosperously in the prognostics field and is being applied with success in prognostics of complex systems or components. The existing research works on the prognostic process demonstrate that the state prediction phase that is actualized by classical procedures, such as particle projection, is always prone to performance degradation. To overcome such a defect, this paper presents a novel technique, named the F-distribution particle filter -based prognostics, following the principle that the particles' weights are calculated dynamically by the F kernel rather than keeping fixing in the state prediction phase. The effectiveness of the proposed approach is evaluated through a real experiment of a hydraulic actuator. The analytical results show that the proposed method is more effective in the prediction of the remaining useful life for the internal leakage fault benchmarked against the existing classical particle filtering-based prognostics.