Age estimation is a crucial part of forensic investigations. Because different parts of the body are often found at crime scenes, it is important to explore the regions that can be used for age estimation. Previous studies have used simple X-ray to analyze changes in costal cartilage calcification as a measure of age. Here, we tested whether age could be better estimated using measurements of costal cartilage calcification on postmortem CT images. In this study, male and female decedents (n = 10 each) from autopsy cases were grouped into 10-year incremental age groups (20-29 y; 30-39 y; up to 89 y). We found that the mean Hounsfield unit (CT number) and percentage calcification (the ratio of the ossified area to the whole area) increased with age for both sexes. However, there were marked individual differences within many of the groups, and this led to a statistically significant difference (P < 0.05) only between the 20-29 y group and the older age groups. To improve the ability to correctly assign cases to age groups, we introduced and reanalyzed the data using Bayesian statistics. This improved the classifications rates, with 40% of males and 35% of females correctly assigned into their age groups. Broadening the age range could further improve the number of matches. Thus, combining Bayesian statistics with CT imaging can be used to estimate age at death from costal cartilage calcification, and could be used as an adjunct in forensic investigations.