eng Oriental Scientific Publishing Company Biomedical and Pharmacology Journal 0974-6242 2026-07-15 19 3 72676 article Gnana Prakasi Oliver Sirya Pushpam 1 Diana Jeba Jingle Issac 1 Kanmani Palanisamy 1 Pari Agarwal 1 Rashi Dubey 1 Aryaman Kant 1 Department of Computer Science and Engineering, Christ University, Bengaluru, India. Coronary heart disease is one of the most common causes of death in the world. Early diagnosis helps us to provide better treatment, which results in the reduction of the mortality rate. Though many machine learning algorithms are in research to predict heart disease, the accuracy in the prediction is still low. To overcome these drawbacks, we apply bagging and boosting techniques to these Machine Learning algorithms. In addition, we hybridize these models by pairwise stacking and three-layer stacking to improve the performance of predication and classification. Results show that the stacking of Machine Learning algorithms with Random Forest gives better results in terms of prediction and classification. https://biomedpharmajournal.org/vol19no3/heart-disease-prediction-with-pairwise-and-three-model-stacking-an-analysis/ Bagging Boosting Coronary Heart Disease Decision Tree Machine Learning Stacking.