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In recent years, the development of deep learning methods have brought new ideas to engine prognosis and health management. CNN has the characteristics of sparse connectivity,shared weights, pooling operation and multi-layer structure. It can effectively extract local features, reduce the training difficulty of the network, and make CNN have strong learning ability and feature expression ability. The prognostic method based on convolutional neural network is studied, and the software platform of the algorithm for engine gas path fault prognosis is realized. Using the test data from engine simulation, verification study shows that prognostic method proposed has better feasibility and effectiveness for the prognostic technology of aero-engine compared with other data-driven prediction methods.