In order to make full use of the advantages of various oil analysis methods and improve the accuracy of wear fault diagnosis of aero-engine rolling bearing, a fuzzy fusion diagnosis method for aero-engine wear fault was proposed.Firstly,according to the characteristics of the respective characteristics of spectral analysis, ferrographic analysis,particle count analysis,physical and chemical analysis data,the oil analysis data were fuzzified based on user-defined membership function,so as to obtain the evidence credibility and rule credibility of characterization spectral analysis, ferrographic analysis,particle count analysis, physical and chemical analysis data, and obtain the comprehensive credibility.Then the D-S evidence theory diagnosis of oil sample data was realized based on the D-S evidence theory.The proposed fusion diagnosis method was applied to aero-engine wear fault diagnosis. The algorithm was verified by using the oil simulation analysis data of a certain engine in different wear periods.The result shows that the proposed method has high diagnosis accuracy and sensitivity.