Cardiovascular Disease is one of the significant dangerous infections in India as well as in the entire world. Cardiovascular Diseases claim around 17.9 million lives each year, making them the leading cause of death. Cardiovascular disease presents a major global health challenge. This project introduces an innovative machine learning framework designed to predict cardiovascular disease and associated risk factors, including hypertension, diabetes, hyperlipidemia, and myocardial infarction. Our system utilizes a Random Forest algorithm trained on a detailed dataset. The project goes beyond prediction by incorporating explainable AI techniques to ensure transparency in model predictions. This allows healthcare providers and patients to understand the contributing factors behind the risk assessments. Personalized health recommendations are generated to help patients adopt better lifestyle choices tailored specifically to their individual data. In addition, the system generates comprehensive reports for each patient detailing the prediction outcomes, risk levels, and suggested precautions. These reports serve as valuable resources for continuous monitoring and further medical consultations. To enhance accessibility, especially for impaired patients, we have integrated pyttsx3 for text-to-speech functionality. This feature reads out the prediction results and recommendations, ensuring that all patients, regardless of their ability to see, can benefit from the system.