With the increasing demand for high power density and compact electronic components, thermal management has emerged as a critical challenge. Accurately predicting temperature under real operational conditions is crucial, as failure to do so can significantly affect both performance and system reliability. This challenge becomes particularly important in modular electrification, which involves complex multiphysics interactions. Existing methods show that solving multiphysics problems often results in increased computational costs, and relying on simplified models makes it difficult to reflect actual operational conditions. To overcome these challenges, this study employs the inverse heat conduction problem (IHCP) for estimating both temperature and heat generation in modular electrification systems. By integrating real operational data with numerical simulations, the proposed methodology effectively captures coupled multiphysics behavior, ensuring reliable temperature predictions under operational conditions [1-4]. The proposed framework is applied to three representative systems—motor drive module, electric steering system, and fuel cell. A model reduction technique is used to enable real-time calculations, making the approach suitable for digital twin applications. The results demonstrate significant improvements in both temperature estimation accuracy and computational efficiency across diverse test cases. This research not only advances thermal management strategies for modular electrification systems but also contributes to the development of robust digital twin frameworks capable of reliable, real-time thermal predictions and informed decision-making. REFERENCES [1] C.-u. Ahn, C. Park, D. I. Park, and J.-G. Kim “Optimal hybrid parameter selection for stable sequential solution of inverse heat conduction problem,” International Journal of Heat and Mass Transfer, 183, 122076. 2022. [2] C.-u. Ahn, S. Oh, H.-S. Kim, D. I. Park, and J.-G. Kim, “Virtual thermal sensor for real-time monitoring of electronic packages in a totally enclosed system,” IEEE Access, 2022. [3] J. -w. Lee, C. -u. Ahn, J. Park, H. S. Kim, C. Park, D. I. Park, and J.-G. Kim, “Heat source and temperature estimation of integrated modular motor drive via inverse heat conduction problem, ” Measurement, accepted. [4] M. N. Özisik and H. R. Orlande, Inverse heat transfer: fundamentals and applications. CRC press, 2021.