In order to solve the problem of randomness and fuzziness of state information in engine state assessment， this paper proposes an aero-engine state assessment method based on combination weighting and cloud model. Through principle analysis， expert experience， and correlation analysis， the hierarchical index system of engine is constructed. The subjective and objective weights are determined by the analytic hierarchy process and the entropy weight method respectively， and then the combination weights are determined by the linear combination weighting method. For the aero-engine to determine the evaluation standard grade and its interval， the state grade score is mapped by the relative deterioration degree， the qualitative analysis is carried out by the cloud model， and the quantitative analysis is carried out by the similarity. The QAR data of multiple engines on the A320 series aircraft are analyzed and verified. The results of the initial use of one of the engines show that： The engine tends from the initial strong discrete health state to the weak discrete sub-health state， and the corresponding parts problems gradually reveal and the actual situation of the running-in period tends to be stable. Therefore， the aero-engine condition assessment model based on combination weighting and cloud model is effective， which provides a strong guarantee for identifying the state of the engine， understanding the long-term trend of the engine， taking preventive maintenance and improving flight safety.