The modeling of high-precision servo mechanisms is complicated by friction nonlinearities, torque fluctuations, and sensor errors, making it difficult to theoretically determine key nonlinear parameters. To address these challenges, a dynamic model of a two-axis servo system incorporating nonlinear parameters was developed. Both inertial and joint nonlinear parameters were identified through system identification. Then, a digital twin model of the servo system was constructed, with its accuracy evaluated using correlation coefficient metrics. Experimental validation was performed on a two-axis test platform by comparing time- and frequency-domain data. The results demonstrate that the digital twin model accurately captures the dynamic characteristics of the system, confirming the effectiveness of the proposed modeling methodology and providing a reliable approach for performance evaluation and control design in high-precision applications.