The detection of brake light plays an important role in applications such as autonomous driving, to avoid rear-end collision. In this work, we propose a frame work to identify the location of two-wheelers and their brake lights in traffic visual data using a deep learning-based approach. The system uses the Yolo object detection model for multi-class detection and localization. The experimental study was conducted on a new dataset of two-wheeler vehicles in traffic.