The Prakruti Dosha prediction model analyses data to predict an individual’s dosha type (Vata, Pitta, Kapha or combination) based on Ayurvedic principles. Users have to input their health-related data, including physical, mental and emotional attributes, through an inherent interface. These parameters will be used as input to the ML model. After the overall execution, the user will be able to know his/her phenotype. Advanced algorithms process this data and accurately determine the major dosha. The model then gives thorough information about the characteristics of the dosha, which helps to balance mental and physical health. Initially, the project used numerous machine learning algorithms, out of which Support Vector Machine (SVM) accomplished a maximum accuracy of 95.05%. To improve the performance of the model, the combinational approach was used by combining Random Forest with Logistic Regression, Random Forest and Naive Bayes models, etc. This model utilises the ability of different classifiers to provide better and accurate Ayurvedic recommendations. Although the results obtained so far are promising, further improvement to develop and improve the model is ongoing. The Prakruti Prediction Model combines conventional Ayurvedic knowledge with the latest tools, offering a comprehensive tool for understanding one’s phenotype and improving overall well-being.