This project focuses on sentiment analysis through facial emotion recognition using artificial intelligence and machine learning techniques. The system combines the Haar Cascade classifier for efficient face detection with a Convolutional Neural Network (CNN) for emotion classification. It can identify emotions such as happiness, sadness, anger, and surprise from images and video streams in real time. The framework provides visual and analytical insights into user sentiments, making it useful for applications like marketing analysis, customer feedback systems, and mental health monitoring. By enabling accurate and efficient emotion detection without requiring extremely large datasets, the project demonstrates the potential of AI-driven facial analysis for understanding human emotional behavior.