Background: Postoperative pancreatic fistulae (POPF) are a major contributing factor to pancreatoduodenectomy-associated morbidity. Established risk calculators mostly rely on subjective or intraoperative assessments. We hypothesized that various objective preoperatively determined computed tomography (CT) measurements could predict POPF as well as validated models and allow for more informed operative consent in high-risk patients. Methods: Patients undergoing elective pancreatoduodenectomies between January 2013 and April 2018 were identified in a prospective database. Comparative statistical analyses and multivariable logistic regression models were generated to predict POPF development. Model performance was tested with receiver operating characteristics (ROC) curves. Pancreatic neck attenuation (Hounsfield units) was measured in triplicate by pancreatic protocol CT (venous phase, coronal plane) anterior to the portal vein. A pancreatic density index (PDI) was created to adjust for differences in contrast timing by dividing the mean of these measurements by the portal vein attenuation. Total areas of subcutaneous fat and skeletal muscle were calculated at the L3 vertebral level on axial CT. Pancreatic duct (PD) diameter was determined by CT. Results: In the study period 220 patients had elective pancreatoduodenectomies with 35 (16%) developing a POPF of any grade. Multivariable regression analysis revealed that demographics (age, sex, and race) were not associated with POPF, yet patients resected for pancreatic adenocarcinoma or chronic pancreatitis were less likely to develop a POPF (10 vs. 24%; p = 0.004). ROC curves were created using various combinations of gland texture, body mass index, skeletal muscle index, sarcopenia, PDI, PD diameter, and subcutaneous fat area indexed for height (SFI). A model replacing gland texture with SFI and PDI (AUC 0.844) had similar predictive performance as the established model (p = 0.169). Conclusion: A combination of preoperative objective CT measurements can adequately predict POPF and is comparable to established models relying on subjective intraoperative variables. Validation in a larger dataset would allow for better preoperative stratification of high-risk patients and improve informed consent among this patient population.