Abstract: There is provided a computer implemented method of training a machine learning model for prediction of unplanned Cesarean Delivery (uCD), comprising: creating or receiving a multi-record training dataset, wherein a record comprises: at least one fetal biometric parameter of a sample fetus obtained by an ultrasonography device, at least one personal parameter of a sample mother of the sample fetus, and a ground truth indicating whether a birth of the sample fetus by the sample mother was a uCD, and training the machine learning model on the multi-record training dataset for generating an outcome indicating likelihood of uCD for a target mother in response to an input of at least one fetal biometric parameter of a target fetus of the target mother and at least one personal parameter of the target mother.