The paper presents a meal planning application designed to help users make healthier dietary choices by providing personalized meal plans based on individual needs and preferences. The application integrates APIs from Edamam and MealDB, giving access to over 1,000 diverse recipes with nutritional information and cooking instructions. The application uses personal attributes such as age, weight, height, gender, and activity level to apply BMI and BMR calculations. Each attribute contributes to modifying and refining the system’s recommendations to match the user’s lifestyle and daily nutrient needs. For example, weight and activity level are closely related to verifying an individual’s energy expenditure. Additionally, the app uses artificial intelligence to enhance meal recommendations, increasing the accuracy of recommendations by 23% compared to traditional methods. Users can track their calorie intake and analyze their eating habits visually. Research shows that the app significantly improves user satisfaction and the effectiveness of meal recommendations.