In today's fast-paced world, many individuals lead modern lifestyles with little time for self-care, leading to serious health issues. The role of food intake in human health is of great significance, and Ayurveda provides a unique approach that blends modern lifestyle and health-oriented habits. At the heart of Ayurveda's approach is the concept of Prakriti, which determines an individual's diet (ahara), lifestyle (vihar), behavior (achara), and remedial measures (parihara) to achieve optimal health. Despite this, many individuals blindly follow media sources recommendations for diet and nutrition, which can result in imbalances in the body without considering their individual Prakriti. The proposed work aims to collect and prepares a meaningful dataset for Prakriti assessment, which will provide insights into the best breakfast, lunch, and dinner diets to suggest. The MLPClassifier, a neural network-based machine learning technique, will be used for Prakriti classification. By integrating knowledge from Ayurveda, machine learning, and human food interaction, the work seeks to raise awareness of the Ayurvedic diet and classify an individual's Prakriti based on their physiological and psychological characteristics.