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Aimed at the characteristics of Prognostic and health management(PHM) in analog circuits，a new method for analog circuit fault diagnostics and prediction based on relevance vector machine(RVM) is proposed in this paper. Firstly, getting frequency domain response by the Monte Carlo Analysis of Analog Circuits, fault features are extracted by wavelet decomposition and reconstruction to make single-fault and double fault diagnosis utilizing relevance vector machine, combining the phase space reconstruction method, the health value of circuit components is represented through calculating the Euclidean distance between output of standard and different parameter analysis, and the trend of health value trajectory with respect to time points can be predicted by training samples of inputs and outputs of RVM, the proposed approach is appropriate for real time prediction in PHM. Simulation results validate the good practicability and effectiveness of the proposed method.