Accurate modeling of complex systems is essential for the development of advanced control strategies. While traditional integer-order models have been widely applied, fractional-order modeling offers superior accuracy in capturing system dynamics. Despite its potential, research on the offline identification of fractional-order models for twin rotor systems remains limited, especially using real-time measurement data. This study addresses this gap by investigating the offline identification of fractional-order models for the elevation and azimuth angles of a twin rotor system based on real-time data. The Fractional-Order Modeling and Control (FOMCON) toolbox in MATLAB is utilized for time-domain model identification. A comparative analysis is conducted between fractional-order and integer-order models, employing MATLAB’s fminsearch function, the explicit (one-time) Least Squares Method (LSM), the Recursive Least Squares Method (RLSM), and its modified variants. Key findings demonstrate that fractional-order models yield superior performance in approximating the elevation and azimuth dynamics compared to integer-order models, achieving improved model fitness and enhanced stability. These results highlight the potential of fractional-order models to significantly improve control system design for twin rotor applications. Overall, the study contributes a robust framework for plant modeling, paving the way for more precise and adaptive control strategies in complex rotor systems.