<p>Nanocrystalline alloys, recognized for their high magnetic permeability, elevated saturation magnetization, and minimal losses, are increasingly favored as core materials in high-frequency transformers. Nonetheless, the magnetic performance parameters of these materials are notably susceptible to temperature variations, which can compromise the precision of magnetic field distribution and loss computation in high-frequency transformers. Addressing this issue, the present study embarks on an analysis of the influence exerted by energetic model parameters on magnetic traits, alongside an examination of the evolution of shape characteristic values in nanocrystalline materials across a spectrum of temperatures. By establishing a correlation between model parameters and the shape characteristic values of hysteresis loops, and considering the intrinsic properties of these parameters, a temperature coefficient is integrated to formulate a temperature-dependent energetic model tailored for nanocrystalline materials. Parameter identification is effectively performed using the particle swarm optimization algorithm, which yields enhanced accuracy in contrast to conventional formula-based models. The model’s validity and practicality are subsequently corroborated through a comparative analysis of simulated and empirical hysteresis loops of nanocrystalline materials at disparate temperatures. This investigation lays down a robust theoretical and empirical groundwork for the simulation of magnetization characteristics in nanocrystalline materials, taking into account thermal factors, and for the accurate calculation of losses in high-frequency transformers.</p>