The case-based decision making method has the advantages of easy to understand and close to the actual decision-making process, so it becomes a hot research topic in the field of decision making. In order to effectively integrate the case information provided by different decision makers (DMs), this paper proposes a case study group decision making model based on consistent weight to solve the multiple attribute classification problem. Firstly, the method builds a mixed integer program ming model based on different case data given by DMs, and identifies the typical case set with maximization of the significance degree of consistent case informaion.Then, the model of maximizing the degree away from the classification threshold is designed to determine the compromise weights and the optimal classification threshold, which is compatible with the DMs. Finally, a case study and a comparison with other methods are provided to verify the feasibility of the method.