In South Africa, distribution transformers (DTs) facilitating solar photovoltaic applications represent the highest percentage of total ownership cost investment for independent power producers (IPPs). One of the most indispensable variables that regulate DTs’ operational life span is the hotspot temperature. The prevailing analytical approaches designated to guesstimate the transformer thermal necessities were fathered in accordance with the conservative foundation that an electrical transformer is prone to uniform mean daily and monthly peak loads. In order to appropriately puzzle out the transformer thermal necessities, the formation of a more detailed thermal model that operates with real-time contorted cyclic loading, ambient air temperature, and the intrinsic characteristics of the transformer in-service losses is required. In the current work, various regression models are proposed for the modification of the top-oil formula and the hotspot temperature formula in the IEEE loading guide standard to replicate the real harmonic load currents (HLCs) and the fluctuating ambient air temperature (AT) on an hourly and daily basis. The proposed thermal model is examined in various transformers case studies, in which the computed outcomes produce an error margin of no more than 3% throughout all test cases when compared to the measured data.