Overweight and obesity pose public health concerns, linked to disease risks, morbidity, and mortality. This study employs machine learning for predictive modeling of obesity or overweight based on physical condition and eating habits data. Various algorithms were tested, with the best performer, random forest, achieving 78% accuracy, 79% precision, 78% recall, and 78% F1-score. This research underscores the potential of machine learning in identifying individuals at risk and aiding healthcare decision-making.

• Obesity Prediction
• Random Forest Algorithm