Demand forecasting is the basic link in the organization of POL support for synthetic brigades, which has a relatively important impact on the successful military operations of synthetic brigades. Because of the particularity of the composition structure of synthetic brigade, the traditional forecasting methods have some drawbacks. Therefore, a demand forecasting method for synthetic brigade based on fuzzy clustering and intuitionistic fuzzy reasoning is proposed. Firstly, the fuzzy C-means clustering algorithm is used to realize the preliminary screening of historical cases in order to improve the speed of case retrieval. Then, the subjective and objective comprehensive weight model of case feature attributes and the case retrieval model based on intuitionistic fuzzy sets are constructed to ensure the accuracy of case retrieval. Finally, a POL demand forecasting model for synthetic brigade based on the overall data characteristics is constructed. The feasibility and practicability of the forecasting method are verified by an example analysis, which proves that the proposed method is helpful to improve the retrieval speed and forecasting accuracy.