This paper introduces a smart and reliable Convolutional Neural Network (CNN) designed to recognize traffic signs in real-time. Trained on the well-known GTSRB dataset, the model works with high-resolution images from cameras mounted on vehicles. It helps cars “see” signs like “Stop,” “Yield,” and speed limits—even when lighting is poor or signs are partially blocked. By using deep learning and advanced image analysis, the system alerts drivers to signs they might overlook, helping prevent accidents caused by missed warnings or speeding. It’s fast, accurate, and fits perfectly into modern driver-assistance systems and self-driving technology. The model shines in tricky spots like school zones, busy intersections, and construction areas where quick decisions matter most. Plus, it’s designed to be flexible and easy to integrate into different vehicle systems. As it learns from more region-specific data, it has great potential to make driving not just smarter, but much safer—wherever the road takes you.