Among the most leading causes of mortality across the globe is infectious diseases. Human Immunodeficiency Virus infection and Acquired Immune Deficiency Syndrome (HIV/AIDS), H1N1 influenza and Poliomyelitis, Severe Acute Respiratory Syndrome (SARS) are all infectious diseases that has cost tremendous lives with the latest being coronavirus (COVID-19) that has become the most recent challenging issue. The extreme nature of this infectious virus and its ability to spread without control, has made it mandatory to find an efficient auto-diagnosis system to assist the people who work in touch with the patients. As Fuzzy logic is considered a powerful technique for modeling vagueness in medical practice, Adaptive Neuro-Fuzzy Inference System (ANFIS) was proposed in this paper as a key rule for automatic detection of chest X-ray Images based on the characteristics derived by texture analysis using gray level co-occurrence matrix (GLCM) technique. The results were promising, reaching 98.67% accuracy compared with the other state-of-the-art techniques.