— Heart disease remains a major health concern worldwide, affecting a large proportion of the global population. According to reports by the World Health Organization (WHO), approximately 17.9 million deaths occur annually due to cardiovascular diseases. In the context of the COVID-19 pandemic and its post-infection complications, cardiac failure has emerged as a commonly observed condition, highlighting the critical need for early diagnosis and prediction of heart disease to enable effective prevention. Timely detection can significantly reduce mortality rates. Recent advancements in machine learning techniques have greatly contributed to the healthcare sector, particularly in the prediction of heart diseases, thereby saving numerous lives. This paper presents an efficient ensemble-based machine learning approach for predicting heart-related disorders, achieving an accuracy of 88.52%.