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We sought to develop a prediction model using prenatal diagnosis codes that could help clinicians objectively stratify a women's risk for delivery-related morbidity. We performed a prospective cohort study of women delivering at a single academic medical center between 2016 and 2019. Diagnosis codes from outpatient encounters were extracted from the electronic health record. Standard and common machine-learning methods for variable selection were compared. The performance characteristics from the selected model in the training data set