Garment purchasing through the Internet has become an important trend for consumers. However, in various garment e-shopping systems, it systematically lacks personalized recommendations, like sales advisors in classical shops, in order to propose the most relevant products to different consumers according to their body shapes and fashion requirements. In this paper, we propose a consumer-oriented recommendation system by fuzzy techniques and AHP, which can be used inside a garment online shopping system like a virtual sales advisor. This system has been developed by integrating the professional knowledge of designers and shoppers and taking into account consumers’ perception on products. It can effectively help consumers to choose garments from the Internet. Compared with other prediction methods, the proposed method is more robust and interpretable owing to its capacity of treating uncertainty.