This study aims at using one of the regression methods to fit a statistical model capable of assessing the risk to undergoing caesarean section operation, provided that certain medical information are known. The information needed for the model can be obtained easily either directly by asking simple questions or from the patient’s history read from given medical record. For this reason, the application of the model does not have to be highly qualified medical professional. Adopting this model can help providing an early warning if the possibility of the risk exists. This is particularly important in case of shortages of advanced medical equipment and/or specialized medical treatment.

The study uses the logistic regression approach, which is suitable for cases where the response variable is binary and the explanatory variables can be continuous, discrete, qualitative, or a mix.

The final model is obtained via a backward stepwise selection using the likelihood criteria. The selected explanatory variables are: number of abortions, the previous exposure to caesarean operation, the level of blood pressure, the level of gestational diabetes mellitus, type of the service (if the service is free or not), fetal weight and the interaction between the mother’s age and the number of her previous pregnancy. The obtained predictive model has the power of correctly classifying 84.3% of the cases. The internal validation of the predictive model was tested using the bootstrapping method.