In this work, we first implement a computational statistics framework for the design optimization of common-drain complementary field-effect transistor (CFET). By using numerical device simulations in combination with statisticall design of experiments (DOE) methodology—specifically the central composite design (CCD)—we construct second-order response surface model (RSM) for all targeted electrical characteristics of CFET. Both the adequacy and accuracy of each RSM are verified through normal residual probability plots and residual-sum-of-squares analysis. These validated models are furthee employed to optimize CFET performance for its circuit applications. By jointly considering threshold voltage, off-state current, on-state current, subthreshold swing, and drain-induced barrier lowering, the structural parameters of the CFET are tuned such that the predicted electrical characteristics approach the desired targets more effectively than that of the nominal design. Moreover, Device simulations of the optimized structures of CFET show strong agreement with the RSM-predicted values, confirming the robustness and accuracy of the developed models. This study represents the DOE-based RSM optimization framework for CFETs, and the formulated equations show highly predictive fidelity, providing a compelling and practical guideline for CFET design prior to high-volume manufacturing.