Abstract: An algorithm and method to provide personal recommendations for nutrition based on preferences, habits, medical and activity profiles for users, and constraints. The algorithm can also be fed and takes into account real-time feedback from the user. The method allows creating a personal nutritional schedule based on a set of constraints, which are solved using an optimization algorithm to find the diet best fitting each user. The method also includes analyzing a single user by applying various statistical techniques, enabling the algorithm to infer the user's preferences and updating of the constraints, analyzing and clustering of the general user population based on statistical principles, giving the algorithm insightful information and allowing improved performance by means of “machine-learning,” and creating a list of recommended food items/recipes to help users live a balanced, healthier lifestyle.