Data-driven modeling and simulation play a pivotal and transformative role in the realm of cyber physical systems (CPS), revolutionizing the way we analyze and understand system behavior within a virtual environment. By harnessing the power of machine learning algorithms, statistical techniques, and data mining methods, data-driven approaches bring forth invaluable insights, unveiling hidden patterns and relationships within vast datasets. This empowers CPS researchers and engineers with an unprecedented ability to comprehensively grasp the intricacies of complex system dynamics. With this newfound understanding, they can optimize system performance, predict potential anomalies, and significantly enhance overall system efficiency and reliability. The embrace of data-driven modeling and simulation signifies more than a mere technological advancement; rather, it represents a transformative shift in our perception and approach to CPS. Its profound impact resonates across various industries, including manufacturing, healthcare, transportation, and energy, fueling innovation and propelling humanity towards a future characterized by heightened intelligence, interconnection, and resilience.