To analyze motion error fields in the rotary axes of a dual-turntable five-axis machine tool, this paper proposes a modeling and identification method for the rotary axis motion errors based on a large-inclination-angle S-shaped test piece. First, based on the machine tool′s topological structure, a motion error propagation model for each rotary axis of the dual-turntable five-axis machine tool is established, along with a rotary axis motion error model that accounts for the coupling effect between the curvature of the S-shaped test piece and its inclination angle. Second, utilizing the dual-standard-sphere identification principle, the virtual circle center coordinates are fitted from two layers of measurement points in the region of maximum curvature of the S-shaped test piece. A method for constructing a virtual standard sphere center based on the virtual circle center is proposed, enabling the identification of the six motion errors of the A-axis （δx(a),δy(a),δz(a),εx(a),εy(a),εz(a)）. Subsequently, a virtual machining model of the dual-turntable five-axis machine tool is built using UG. The milling process of S-shaped test pieces with different inclination angles is simulated. Combining the simulation results with on-machine measurement experiments, the influence of large inclination angles on the identification results of A-axis motion errors is analyzed, revealing the sensitivity of the S-shaped test piece′s inclination angle to A-axis motion error identification. As the inclination angle increases, the identified values of each A-axis motion error exhibit a trend of first increasing, then decreasing, and finally increasing again. Compared with the S-shaped test piece without an inclination angle, the identification accuracy of the six A-axis motion errors is improved by approximately 10% for inclination angles between 45° and 60°. Finally, based on the identified A-axis motion errors, the Kriging interpolation method is used to establish the motion error field of εz(a), which is the most sensitive to inclination angle in the machining workspace of the five-axis machine tool. The results show that, under different rotation angles of the A-axis, the motion error εz(a) of the dual-turntable five-axis machine tool exhibits a stable distribution pattern, with smaller values in the center and larger values near the edges. This finding provides a reference for precision optimization and error compensation of five-axis machine tools under large posture variation machining conditions.