To model craniofacial malformations caused by vitamin A deficiency (VAD), we expressed a dominant-negative retinoid receptor mutation in osteoblasts to specifically inhibit RAR transcriptional activity in mice. This approach allowed us to investigate the effects of VAD on cranial hypomineralization, mandibular deformity, and clavicular hypoplasia in clinical cases. In this study, microcomputed tomography (microCT) scanning of the craniomaxillofacial region of mice represented a valuable tool for studying the growth and development of this animal model. The manual estimation of images is both time-consuming and inaccurate. Hence, here, we present a straightforward, efficient, and accurate approach for segmenting and quantifying the microCT images of each craniomaxillofacial bone. MicroCT software was used to slice the mandible, frontal bone, parietal bone, nasal bone, premaxilla, maxilla, interparietal bone, and occipital bone of mice and measure their corresponding lengths and widths. This segmentation method can be applied to study growth and development in developmental biology, biomedicine, and other related sciences and allows researchers to analyze the effects of genetic mutations on individual craniofacial bones.