Tang Dynasty female terracotta figurines, as important relics of ceramics art, have commonly suffered from natural and man-made damages, among which facial damage is severe. Image inpainting is widely used in cultural heritage fields such as murals and paintings, where rich datasets are available. However, its application in the restoration of Tang Dynasty terracotta figurines remains limited. This study first evaluates the extent of facial damage in Tang Dynasty female terracotta figurines, and then uses the Global and Local Consistency Image Completion (GLCIC) algorithm to restore the original appearance of female terracotta figurines, ensuring that the restored area is globally and locally consistent with the original image. To address the issues of scarce data and blurred facial features of the figurines, the study optimized the algorithm through data augmentation, guided filtering, and local enhancement techniques. The experimental results show that the improved algorithm has higher accuracy in restoring the shape features of the female figurines’ faces, but there is still room for improvement in terms of color and texture features. This study provides a new technical path for the protection and inpainting of Tang Dynasty terracotta figurines, and proposes an effective strategy for image inpainting with data scarcity.