Craniofacial reconstruction is used to estimate facial data for a given unknown skull data, and it has been widely applied in various fields such as forensic science, anthropology, and criminal investiga. tion. It is time-consuming and laborious to extract feature points manually during craniofacial reconstruc. tion. In this study, radial curves uniformly distributed on the face were automatically extracted starting from the nose tip as a feature representation of the three-dimensional craniofacial model based on its geome. try structure. The extracted radial curves and skull data were used as training sample data to establish a sta. tistical model for craniofacial reconstruction. Previous knowledge obtained using the statistical model and skull data were used to estimate the data for the face. The experimental results showed that when the craniofacial statistical method based on the radial curves was applied, the craniofacial reconstruction accuracy improved by 2. 95 times;moreover, the reconstructed speed was 4. 01 times faster than that of the cranio. facial reconstruction method based on principal component analysis. Therefore, our method reduces the di. mension of craniofacial data and improves the accuracy and speed of the reconstruction results.