This capstone project investigates the determinants of used-car prices and evaluates which predictive modeling technique - linear regression, decision tree, or neural network, produces the most accurate and reliable price predictions. The business problem examined is: Which vehicle characteristics most strongly influence used-car prices, and which predictive modeling technique provides the most reliable results? This question is highly relevant for used-car dealers seeking data-driven pricing strategies.