<p>The popularity of fuzzy logic is mounting throughout the world because of hybrid intelligent systems during the last five decades with the assistance of fuzzy logic inference engine. A lot of research has been conducted on chronic diseases with the aid of fuzzy logic but has yet to produce a celiac disease diagnostic system with the support of fuzzy logic. Celiac disease is diagnosed with clinical tests but with this proposed system, the system can deliver recommendations and celiac disease prediction based on symptoms. The proposed system will be executed in MATLAB and Python (PyCharm), which produces 92% probability of celiac disease in MATLAB in comparison with 96.15% probability of celiac disease in Python. So, Python results are more reasonable in comparison with MATLAB results in the proposed system in terms of accuracy. The proposed system produces 98.66% accuracy, 98.21% sensitivity, 94.83% precision of the fuzzy system having an error rate of 1.33%. 55 celiac patients (21 males and 34 females) were identified from the study of 300 individuals. The system is intended to support clinical decision-making and should be used as a as a supportive clinical decision support tool alongside standard diagnostic procedures. <i>Relevance of Work</i> As multiple expert systems accessible everywhere in the world for diagnosis various diseases, fuzzy logic is useful to diagnose celiac disease which will be propitious for society as well as for physicians to predict celiac disease with symptoms; and used as a supportive clinical decision support tool.</p>