Addressing the adverse effects of dietary problems caused by imbalanced nutrition and poor food combinations on people?? s physical and mental well-being particularly concerning research on the relationship between diet and chronic diseases an intelligent system capable of recommending sound and nutritionally balanced meals tailored to users?? conditions preferences and tastes was designed and developed. Methods A nutrition meal recommendation system based on an artificial intelligence knowledge base was constructed. It utilized a definitive dataset of diets validated by experts combined with a reasoning decision support system RDSS and a nutritional plan NP employing NAct ontology to provide highly accurate dietary plans. It spanned 10 user groups including healthy subjects and participants with health problems. Results The effectiveness of the system was assessed through extensive experiments which involved synthetic data including the generation of 3 000 virtual user profiles and their weekly dietary plans. The results indicated high precision and recall rates for recommending appropriate ingredients across most user categories with the dietary plan generator achieving an overall recommendation accuracy of 94% for all nutrients. Conclusion The nutrition meal recommendation system based on an artificial intelligence knowledge base can personalize recommendations based on users?? physical conditions preferences dietary restrictions and other aspects. Such personalized recommendations can better meet users ?? needs thereby enhancing the accuracy of the recommendations. The expert knowledge base encompasses extensive nutrition and health knowledge which can assist the system in identifying the most suitable dietary plans for users. These plans not only provide ample nutrition but also avoid foods or ingredients incompatible with users?? health conditions.