Using Machine Learning to Predict Chronic Diseases Predicting chronic diseases such as diabetes, cardiovascular disorders, and hypertension represents a major healthcare challenge due to their long-term impact. Machine learning contributes by analyzing patients’ historical health data, including age, lifestyle factors, and biometric indicators, to identify patterns associated with disease risk before symptoms appear. Predictive models rely on algorithms such as logistic regression, random forests, and neural networks trained on historical medical datasets to detect risk factors. Early prediction enables preventive interventions that reduce disease progression and complications. Wearable devices also collect continuous health data, such as heart rate and physical activity, which are analyzed using AI algorithms to detect abnormal patterns. Integrating machine learning into preventive healthcare supports proactive medicine and reduces pressure on healthcare systems. Al-Mustaqbal University is ranked first among Iraqi private universities