WCE stands for Wireless Capsule Endoscopy. It is a cutting-edge medical image visualisation technique that makes the gastrointestinal (GI) system visible. With WCE, a tiny capsule that is usually fitted with a tiny camera, and light source is swallowed and travels through the digestive system, taking high-definition pictures of the GI tract along the way. WCE is primarily used to diagnose a variety of GI tract disorders and anomalies, including ulcers, tumors, and bleeding. The utilization of Wireless Capsule Endoscopy (WCE) for visualizing the patient’s digestive tract generates a significant volume of data, which requires a considerable amount of time and specialized expertise for thorough analysis. Even though WCE is a great tool, finding and pinpointing areas with bleeding regions are still a big challenge. The proposed model named Wireless Capsule Endoscopy Images Classifier (WCEIC) is based on a combination of MobileNet features and color histograms for classifying gastrointestinal bleeding images. Its promising performance metrics underscore its potential utility in assisting medical professionals in the diagnosis and analysis of gastrointestinal disorders. Dataset comprising 2618 Wireless Capsule Endoscopy (WCE) images was employed to train & test the model. The evaluation of the model’s performance utilized metrics such as accuracy, precision, recall, F1 score. Results.