Approximately 800 fetal losses occur each year in the United States due to motor vehicle crashes. Changes during pregnancy drastically alter the abdominal anatomy of the pregnant female. Pregnant occupants involved in motor vehicle crashes are at risk for pregnancy-specific injuries, such as placental abruption. In this study, anthropometry data is collected from an abdominal CT scan of a pregnant woman at 32 weeks gestation. A scan most representative of a fifth percentile female in the early 3rd trimester with a healthy fetus and no abdominal injury was selected for analysis from available abdominal computed tomography (CT) scans taken over the past ten years. Using medical image analysis software, masks of the fetus, uterus, placenta, and each of the maternal abdominal organs are created by segmentation of the CT slices. The volume and Hounsfield unit ranges for the masks of each abdominal organ are calculated. The total volume of the uterus is 3378 cm3. The total volume of the placenta is 687.7 cm3. The masks are used to render three-dimensional volumes of each of the organs. By measuring the length of seven different sets of bones on the fetal skeleton from the CT slices and the 3D rendering, the gestational age of the fetus is estimated to be 32.2 ± 1.9 weeks by comparison with literature values, which matches the estimated gestational age of 32 weeks predicted by emergency room staff. Anthropometric measurements confirm the woman is within one standard deviation of 5th percentile. Measurements of each of the abdominal organs are obtained from the 3D rendering to create a blueprint of the pregnant anatomy. The uterine wall thickness is found to differ in the superior-inferior direction, with average uterine wall thickness 6.80 ±0.72 mm. The placenta thickness varies along its attachment at the UPI and is thickest at the fundus. After creating an accurate FE model of the UPI, improved geometry may help to predict the occurrence of placental abruption. The masks created and the anthropometric measurements taken will be used to develop a more accurate FE model of the pregnant female for use in research and development in academia, industry, and government.