The combination of Internet of Things (IoT) data and machine learning has transformed the prognosis of cardiovascular health. Wearables, smart sensors, and continuous monitoring generate real-time, personalized data. Machine learning deciphers intricate patterns, predicting cardiovascular events accurately. Traditional risk assessments rely on periodic checks, missing crucial changes. IoT, coupled with machine learning, enables continuous monitoring, detecting subtle variations. This proactive approach empowers early interventions, personalized treatments, and lifestyle recommendations. Predictive modelling using IoT and machine learning shifts healthcare from reactive to proactive, aligning with precision medicine goals. Despite promising outcomes, challenges like data security and interdisciplinary collaborations need addressing.