Heart disease is one of the main causes of death worldwide and must be diagnosed and prevented as early as possible. This paper proposes a novel Heart Disease Prediction Bot to scan health data given by the users, which contains ECG reports, and then present actionable recommendations with cutting-edge technologies. The system includes Streamlit for the interactive front-end interface, Gemini AI for natural language processing and predictive analytics, and EasyOCR for extracting text from medical images uploaded by users. This solution includes Matplotlib to visualize risk distribution and Pyttsx3 for text-to-speech conversion, making the system more accessible. The input given by users for critical health metrics such as age, cholesterol levels, and ECG results are processed by the bot in order to predict the chances of heart disease and make recommendations to individuals for improving their health. It addresses the system architecture, implementation, and performance issues in its capability to aid both healthcare providers and individuals who start showing signs of heart disease. The solution to be presented tackles the gap created between available technologies in health care and the prevention of cardiovascular disorders.