The multi-classification discrimination model based on unbalanced Cardiotocography (CTG) data is built by Deep Forest (DF) framework. The validity of the model is verified, and the results show that the prediction performance of the model is good, the misjudgment rate is greatly reduced, and the model has a good application prospect in the intelligent assessment of antenatal fetal health status.