In this paper, the model for a multi-sensory food recommender is presented, which takes into account both taste and aesthetic attributes of food. The recommender was designed using a case-based reasoning (CBR) approach, and built with the myCBR framework. The recommender was later integrated into an Android application prototype, via which potential user feedback was obtained. We conducted a preliminary user study in which all participants rated their satisfaction with the recommendations above 5 on a scale of 0 to 10. Furthermore, 72% of participants felt that by considering their aesthetic preferences in the recommendation process, the system produced better recommendations than if they were not considered.