OBJECTIVE : The aim of this study was to develop an accurate and intuitive semi-automatic segmentation technique to calculate an average maxillary arch and palatal growth profile for healthy newborns in their first year of life. METHODS : Seventy babies born between 1985 and 1988 were included in this study. Each child had five impressions made in the first year after birth that were digitalized. A semi-automatic segmentation tool was developed and used to assess the maxillary dimensions. Finally, random effect models were built to describe the growth and build a simulation population of 10,000 newborns. The segmentation was tested for inter- and intra-observer variability. RESULTS : The Pearson correlation coefficient for each of the variables was between 0.94 and 1.00, indicating high inter-observer agreement. The paired sample t test showed that, except for the tuberosity distance, there were small, but significant differences in the landmark placements between observers. Intra-observer repeatability was high, with Pearson correlation coefficients ranging from 0.87 to 1.00 for all measurements, and the mean differences were not significant. A third or second degree growth curve could be successfully made for each parameter. CONCLUSIONS : These findings indicated this method could be used for objective clinical evaluation of maxillary growth. CONCLUSIONS : The resulting growth models can be used for growth studies in healthy newborns and for growth and treatment outcome studies in children with cleft lip and palate or other craniofacial anomalies.