Industry 4.0 is a high degree of connection and integration of information and mechanical equipment. The goal of Industry 4.0 is to link equipment, production lines, factories, suppliers, products, and customers closely. With the continuous increase of smart manufacturing equipment, the responsibility of the purchasing department and purchasers will become heavier. Therefore, purchasers must understand these kinds of equipment and their functions in order to make a good decision. The objective of this paper is to establish a procurement decision support model. It presents corporate purchaser decision-making criteria as reference for the food processing machinery (FPM) manufacturing industry. Combining the concepts and methods of mean-end chain (MEC) and fuzzy analytic hierarchy process (FAHP), an MCDM model to select suitable machinery for the food processing industry was presented. Firstly, a hierarchical structure includes 2 factors, 7 criteria, and 25 subcriteria for FPM purchasers to select machines is constructed based on MEC analysis. Secondly, FAHP is used to solve the subjective weights of all criteria and subcriteria. Then, the key factors of FPM procurement were obtained. There are 50 FPM purchasers to be interviewed in first phase, and 50 AHP questionnaires were distributed to these purchasers in second phase. Fuzzy multicriteria decision analysis was carried out, and the top five most important attributes out of the 25 criteria were sorted out. They are switching cost, price, brand, professionalism of service personnel, and accessibility of after-sales services. This study uses actual industrial cases to verify the proposed method, and offers the practical purchasing decision support model based on the actual FPM purchaser and the manufacturer’s product manager. It will enhance the practicality of the research. In addition, the lack of the literature makes it difficult to establish an evaluation model. This study uses MEC and FAHP to obtain evaluation criteria and establish evaluation models, which will be the original contribution of the research.