The Digital Twin (DT) concept lacks a unique definition, as it varies depending on the application field. A DT embodies the virtualization of a physical asset and plays a vital role in real-time prediction, optimization, monitoring, control, and informed decision-making. It enables reactive, preventive, predictive, and prescriptive maintenance while facilitating efficient data processing and rapid simulations. In the aerospace industry, creating high-fidelity models is crucial for enhancing new aircraft’s preliminary design, performance, and safety. A digital twin can support shifting from analytical methods to estimate stability and element dimensions, addressing challenges like digital transformation, high production operation costs, low maintenance efficiency, and intensive technology (Xiong and Wang in Int J Adv Manuf Technol 121:5677–5692, 2022 [1]). The Next Generation Air Dominance encompasses high-fidelity physical models and avionics software, requiring a digital representation. West et al. (Procedia Comput Sci 114:47–56, 2017 [2]) provides insights into establishing a platform for digital twinning in the aerospace industry. Improving models to construct high-fidelity digital twins is imperative. Despite utilizing significant computational resources, such as Computer Fluid Dynamics (CFD), the Reduced Order Model (ROM) enables accurate and swift simulations of factors like aerodynamic loads. (CFD based ROMs for aeronautical applications, 2016 [3]). Essentially, the digital twin can be employed to validate the data required to estimate the dynamic performance of aircraft. This study is interested in a glider scenario resembling a game simulation. By conducting CFD simulations, enough variables of interest are obtained, enabling the creation of a ROM and, subsequently, the digital twin. This approach showcases the advantages of employing the ROM and digital twin for evaluating aircraft performance and aerodynamic loads.