I conducted a data-driven study on predicting and understanding hair loss using a combination of data visualization and machine learning. The project explored how factors such as age, stress, medical conditions, and nutritional deficiencies contribute to hair loss. Using techniques like logistic regression, random forest, and clustering, I analyzed patterns, identified key risk factors, and provided actionable recommendations for prevention and early intervention.