Stroke prediction is critical in healthcare, as it can significantly impact patient outcomes. This study explores the use of machine learning approaches to predict strokes among both young and elderly patients. By analyzing different factors, we aim to develop a robust model to aid in early detection and prevention. According to the World Health Organization (WHO), stroke is the second leading cause of death globally, accounting for about 11% of all deaths. Thus, the stroke prediction technique with high accuracy would be essential.Machine Learning technique would be the most common technique used to the early prediction in health care area, thus, we aim to use and compare different machine learning method to predict stroke occurrence.