The Lung Cancer Prediction System employs an Artificial Neural Network (ANN) to enhance the accuracy and efficiency of early lung cancer diagnosis. This intelligent system processes diverse patient data— including medical history, lifestyle factors, and diagnostic results—to identify patterns indicative of malignancy. The ANN model is trained on a comprehensive dataset of historical patient records, enabling it to distinguish between benign and malignant conditions by learning complex data relationships. As it continues to receive updated data, the system refines its predictive capabilities, ensuring continuous improvement over time. By enabling earlier detection, the system supports more prompt clinical intervention, potentially saving lives. This approach signifies a shift in medical diagnostics by integrating advanced machine learning methodologies for proactive healthcare management.