Abdominal colic is pain in the stomach caused by enlargement, blockage, or inflammation of organs in the body. Frequently, abdominal pain is mistaken for common gastritis. This has led to 259 million undiagnosed cases of appendicitis in men. Most cases of abdominal colic require surgical intervention, as it encompasses several diseases with similar symptoms. During surgery, doctors sometimes discover other types of diseases in patients, which adds to the time and effort required. The urgency of this research can impact the concentration and performance of doctors during surgical procedures, increasing the risk of complications that may result in fatalities for the patients. The proposed solution for this research is the implementation of an expert system based on a web application model. The research stages include data collection, data processing, interpolation method, certainty factor method, and testing. This research combines the certainty factor and interpolation methods for diagnosing abdominal colic diseases using 29 symptoms and 14 diseases. It also incorporates user belief values customized to the user's consultation form. The interpolation method is used for laboratory results, while the certainty factor method is applied to the anamnesis and physical examination. The research findings show an accuracy of 96%, with 96 patients accurately diagnosed by the system compared to the original data from 100 test patients at the Qadr Tangerang hospital.