Background Abdominal Wound Dehiscence (AWD), occupying a large proportion of neonatal surgery is an essential complication of abdominal surgery, which can leads to severe consequences, including life-threatening. This study aims at exploring prediction value for AWD with potential joint factors of hypoproteinemia and incision type. Method The Cox proportional-hazards model (the Cox model) was applied to analyze clinical data came from 453 patients underwent neonatal laparotomy from June 2009 to June 2020. According to application of the random numbers, 453 cases were divided into two separate models randomly involving training set with 318 observations (70%) and validation set with 135 observations (30%), and then the models trained were validated based on the validation set. Investigation in the connection between hypoproteinemia, incision type, combined factors and AWD, were used for comparing those prediction values for AWD. Results With a median follow-up of 15 months, the incidence of neonatal AWD was 6.0% (27/453). Based on the univariate and multivariate Analysis using the Cox Regression Analysis, hypoproteinemia(HR = 7.005, P = 0.001) and joint factor༈HR = 6.901, P < 0.001༉were both the independent risk factors for neonatal AWD in training set. Meanwhile, hypoproteinemia and joint factor༈HR = 5.497, P = 0.045༉were both also the independent risk factors for neonatal AWD in validation models, which indicated that joint factor was the independent risk factor in both models. The summary ROC curve was estimated, and the area under the ROC curve (AUC) was calculated as a criterion for validating the models trained. The findings illustrated that AUC of joint prediction factor for AWD was higher than either that of hypoproteinemia༈0.759 vs. 0.638) or incision type factor ༈0.759 vs. 0.671༉singly. Conclusion The contribution of hypoproteinemia and incision type combined factor for predicting AWD is superior than that of them individually, resulting in a significant promotion in prediction efficiency and accuracy of predicting neonatal AWD.