Despite fuzzy logic has been utilized in healthcare difficulties; there are still some rare disorders that require adequate implementation through fuzzy logic. Without clinical tests, it is incredibly challenging for any physician to distinguish celiac disease from some of the other auto-immune disorders. As a consequence, developing such an intelligent system to diagnose celiac disease without laboratory testing and provide insight and recommendations for clinical evaluation. This proposed approach utilizes a hybrid of machine learning and fuzzy logic. The Fuzzy logic toolset provides a fuzzy inference analysis to determine input–output parameters. The implementation has been done in Python using the PyCharm tool; 113 celiac patients were found in the study with 97.708% accuracy, error rate of 2.292%, and sensitivity outcome of 94.95% of the fuzzy system using fuzzy if–then rules. This proposed fuzzy system will be beneficial for medical experts to diagnose celiac disease without clinical testing.