Due to the extensive growth of food variety and hectic lifestyles, people have been facing the issue of making healthy food decisions to reduce the risk of diseases. In this context, food recommender systems can encourage users to change their eating behaviors or suggest healthier food choices. Food recommendation systems’ primary objective is to analyze users’ eating habits and persuade them to adopt healthier ones. Food recommendation systems are designed to identify and predict only those foods that a corresponding user is most likely to want to eat and are also healthy. Food recommendation systems are emerging in online food services to recommend healthy food to users based on their previous diets. Although unhealthy diets may cause challenging diseases such as diabetes, cancer, and premature heart disease, many food recommender systems have been developed to address these issues. These food recommender systems not only recommend foods that meet users’ preferences but also recommend foods with nutritional value, track eating habits, identify health problems, and convince users to change their eating behavior. This chapter covers all the concepts related to healthy food recommendation, an application domain of healthcare recommender systems. We have also discussed some techniques for data collection, filtering techniques used for the healthy food recommendation and evaluation metrics to evaluate the performance of the recommender systems. This chapter concludes with healthy food recommendations, challenges, and attainable future scopes.