Abstract: In view of the current imbalance in the development of the airport group, the international hub airport has a high delay rate, the flight time is short, the resources are tight, but the regional hub airport has the problem of idle resources. An airport group delay prediction model based Skip-LSTM is proposed. Firstly the information of each airport in the airport group, the flight information and the weather information of the airport group area are integrated and processed in the model, then the feature information of the merged data is extracted in the Skip-LSTM network model. Finally, the Softmax classifier is used to classify and predict. The Skip gate is added to the Skip-LSTM based on the traditional LSTM, which can more fully extract the time correlation of data information. The higher accuracy is obtained in the model. The experimental results show that the accuracy of the airport group delay prediction model based on Skip-LSTM can reach 95.35%, and the prediction performance is better than the traditional network model, which can effectively predict the delay of the airport group.