The maintenance and time-to-time analysis of the power transformers are essential to maintain the reliability of the supply. Unfortunately, the operating power transformer is constantly subjected to various electrical and thermal stresses, leading to mineral oil and cellulose paper insulation degradation. Consequently, the decomposition of mineral oil gives rise to different gases that dissolve in the oil itself. These gases indicate various incipient faults, which, if neglected, lead to catastrophic failure of the transformer. Therefore, in this proposed work, the well-acclaimed dissolved gas analysis (DGA) method is used to diagnose the transformer. Innumerable techniques were proposed in the past literature, yet the diagnosis wavers and no single method could provide an unambiguous diagnosis. Besides, a blend of produced gases results in inaccurate diagnosis when gas ratio methods are utilized. This work proposes a fuzzy-based DGA approach to harness the limitations and homogenize the diagnosis. Mainly, this work has been focused on the fuzzy-based IEC ratio method to interpret the incipient faults as the IEC ratio method persuasively isolates disparate incipient faults. DGA results of various transformers of different ratings and life span are used to build the model. The obtained outcomes unveil that the fuzzy-based DGA is effective to diagnose the transformers properly.