e health index scheme can be the most fundamental tool that unifies all transformer condition status information into a singular outcome, thereby enhancing the power transformer asset management and life longevity strategies. is study aims at establishing a multiple parameter-dependent transformer health index estimation model cascaded with a fuzzy logic inference system. is strategy is centered on the effect of dynamic loading regime, varying hotspot temperatures and multiple attesting results of the insulation system. Furthermore, a nonintrusive degree of polymerization (DP) model based on furans and carbon oxide ratios as DP pointers is also factored in developing the health index model. e general outcome of the health index depends on entirely considered elements, but not on any isolated attribute. Data obtained from in-service transformers were used to validate the proposed model. e outcome of the model mirrors the practical condition of the evaluated transformers. erefore, the proposed health index model can be a vital tool to asset managers and power utilities.