The Diet Recommendation System Based on Blood Parameter Levels is an intelligent health support application designed to suggest personalized diet plans according to an individual’s blood test results. The system analyses key blood parameters such as glucose, haemoglobin, cholesterol, and protein levels to assess nutritional deficiencies or imbalances. By applying data analysis and machine learning techniques, the system interprets the health condition and generates suitable dietary recommendations to help users maintain or improve their health. This system uses Python as the core programming language, along with libraries like Pandas, NumPy, and Scikit learn for data processing and predictive modelling. A Flask based web interface enables users to input their blood parameter values and receive customized diet suggestions in real time. The integration of Google Generative AI (Gemini) further enhances accuracy and personalization by analysing broader dietary patterns and medical insights. The project aims to promote preventive healthcare by encouraging healthy eating habits based on scientific data. It provides a convenient, cost-effective, and user-friendly platform that bridges the gap between medical diagnostics and nutritional guidance. Ultimately, this system contributes to early detection of potential health risks and supports users in achieving better lifestyle management. A Flask based web interface allows users to input their blood test results and receive instant dietary suggestions in a user-friendly manner. To enhance intelligence and personalization, the system integrates Google Generative AI (Gemini), which helps in refining recommendations based on large scale nutritional datasets and current health guidelines.