The integration of smart materials into adaptive building structural systems has emerged as a transformative approach to achieving resilient, energy-efficient, and responsive infrastructure. These materials—such as shape memory alloys, piezoelectric ceramics, and magnetorheological fluids—possess inherent capabilities to sense, respond, and adapt to environmental stimuli, offering dynamic control over structural performance. As buildings evolve into intelligent systems capable of interacting with their environment, there is an increasing need to model and optimize these materials at multiple scales to fully harness their potential. Multiscale modeling provides a comprehensive framework that links material behavior from the microscale (e.g., molecular or crystalline structure) to the macroscale (e.g., structural response), enabling accurate prediction of performance under various loading and environmental conditions. This approach allows engineers to understand the intrinsic properties of smart materials and their interactions within complex structural systems, supporting design decisions that balance mechanical performance, cost, and energy efficiency. Recent advances in computational methods, including finite element analysis, homogenization techniques, and machine learning- assisted modeling, have significantly enhanced the fidelity of multiscale simulations. These tools enable performance optimization through parameter tuning, structural health monitoring, and adaptive control strategies. However, challenges persist in integrating diverse scales, ensuring model validation, and addressing real-time computational demands in building applications. This paper presents a detailed review of current methodologies in multiscale modeling of smart materials and explores their application in adaptive building structures. It emphasizes the role of performance optimization in improving energy adaptability, structural resilience, and functional longevity, providing insights into future research directions that bridge materials science, structural engineering, and intelligent control systems.