Aiming at the multi-attribute group decision-making problems with Vague value and considering the reliability of expert rating, a multi-attribute group decision-making analysis method based on Vague set fuzzy entropy and D-S evidence theory was proposed. The method took into full account the fuzziness and uncertainty embedded in the Vague value evaluating information given by various experts, and used fuzzy entropy to obtain the scoring credibility sequence matching experts'opinions. It is completely data-driven, which makes up for the deficiency of the traditional method in the subjective unified setting of credibility. Firstly, based on the original decision matrix of each expert, the fuzzy entropy of Vague set under each attribute was obtained to construct the scoring credibility matrix corresponding to the expert set. Secondly, the information of each expert decision matrix adjusted by credibility was gathered through evidence synthesis, and the attribute weight was obtained by using score function of Vague sets and credibility adjustment. Finally, the final Vague evaluation value of each scheme was calculated by modifying the aggregation information of expert group by attribute weight, and then the comprehensive score of each scheme was obtained by using the score function to screen the optimal scheme. By using the advantages of evidence theory in uncertain information fusion and the information transformation function of score function of Vague sets, the evaluation information of expert group was gathered through evidence synthesis and score function of Vague sets, the decision-making results were more objective and reasonable, and the feasibility and effectiveness of the proposed method were verified by a specific numerical example.