The invention discloses a fresh agricultural product recommendation method based on multi-granularity fuzzy data. The method comprises the steps of obtaining feature parameters of a user and a product; constructing a feature model based on the feature parameters so as to determine user preference parameters; and inputting the user preference parameters into a multi-granularity fuzzy data recommendation model to obtain a recommendation result, and feeding back the recommendation result to the user. According to the scheme provided by the invention, the user satisfaction is considered based on the similarity between the user preference product and the recommended product. Therefore, in the recommendation process, products meeting the preference behaviors of the user can be recommended, and the optimal recommendation can be generated for the user on the basis. Compared with a current fresh agricultural product e-commerce platform, the method has great practical significance, the conversion rate can be increased, higher benefits can be brought, the user experience can be improved, the user viscosity can be enhanced, and therefore the method has outstanding emphasis in the increasinglyintense market of current fresh agricultural product e-commerce competition.