Abstract: The boundary element method (BEM), as a numerical approach based on integral equations, has been widely applied in the simulation of head-related transfer functions (HRTFs). However, its preprocessing still requires manual mesh construction, which not only consumes human effort but also compromises the reproducibility of the simulation results. In this study, a representative head mesh template was selected based on morphological correlations of human head shapes, enabling a series of automated preprocessing steps including coordinate alignment, mesh refinement, and source placement at the ear canal entrance, to simplify the computational model and enhance both model processing and HRTF calculation efficiency. Results obtained from the template-based preprocessing demonstrate that, compared with manual processing, the model mesh exhibits a consistent vertex sequence, with rotational and translational errors of the model coordinate system within approximately 3° and 3 mm, respectively, and discrepancies in ear canal source positions not exceeding 2.5 mm. The entire modeling procedure is fully automated by computer, and its time consumption is negligible compared with manual processing. Further analysis indicates that the template-based computational model reduces the calculation time of full-sphere HRTFs by approximately 55%, while maintaining spectral errors within 1.0 dB below 16 kHz, and interaural time difference (ITD) deviations confined to the lateral directions and less than 10 μs. Finally, validation with a virtual auditory localization model confirmed that no significant differences exist in the localization outcomes of HRTF derived from the two modeling methods. These findings demonstrate that the proposed modeling approach significantly improves the efficiency of HRTF numerical computation without sacrificing accuracy, while optimizing and standardizing the preprocessing workflow of computational models, making it suitable for large-scale personalized HRTF simulations.