Abstract: To address the issues of fuzziness and randomness in assessing the health status of hydropower units, and considering the variability and complexity of their operating conditions, we propose a health evaluation model based on an improved G1-CRITIC method and Gaussian interval membership.First, a comprehensive evaluation index system for the health status of the units is established based on their structural characteristics and operating principles.Next, a combined weighting model is constructed using the improved G1-CRITIC method, which takes into account both the correlations among indicators and expert judgment, thereby optimizing the integration of subjective and objective weights.Subsequently, the Gaussian threshold method is applied to quantify the evaluation indicators for equipment maintenance effectiveness and calculate the degradation degree of each indicator.Finally, the degradation degree of the health status indicators is incorporated into an improved fuzzy membership model to derive the fuzzy evaluation matrix for each indicator and obtain the overall fuzzy state evaluation matrix for the target hydropower unit.The membership functions and comprehensive scores before and after maintenance are then generated, enabling a quantitative evaluation on the health status of hydropower units.The proposed method′s effectiveness in accurately assessing the health status of hydropower units under different operating conditions is validated through practical case studies in an actual hydropower plant.