 This study compared two deep learning models, DenseNet 169 and ResNet 152, to determine their effectiveness at detecting and classifying maxillofacial fractures in CT scans. Both models achieved high accuracy weights, with DenseNet 169 achieving an overall accuracy of 0.70 and faster RCNN achieving an overall accuracy of 0.78. These results suggest that both models are capable of accurately identifying maxillofacial fractures in CT scans. This article was authored by criticism Warren, Wasit Limprezit, Siriwan Swetnookin, and others.