A heterogeneous multi-attribute decision-making method based on Case-Based Reasoning and Grey Correlation Analysis is proposed to solve the issue of the inability to accurately push similar cases in case retrieval with heterogeneous information, considering the ambiguity of decision information and the interaction of attributes, in order to improve the accuracy and efficiency of case retrieval. Firstly, the generalized Shapley values under different attributes are calculated based on fuzzy measures to reflect the correlation between attributes and their weight information. Secondly, based on the idea of case-based reasoning, the grey relational model is used to calculate the similarity between the target case and the historical case. In addition, by combining the generalized Shapley value with grey correlation, the grey correlation degree between the target case and historical case is obtained, thereby obtaining processing measures that can be referenced by the current target case. Finally, the feasibility and practicality of the proposed method are verified through the case retrieval problem of judicial enforcement cases, which can improve the heterogeneous multi-attribute decision-making theoretical system, broadening new paths to solve difficulties in the judicial field.