The disruption recovery is regarded as a crucial role in the operation of freighter airlines. To expand the application scenarios of the freight flight network, elements such as mandatory nodes and external arcs were introduced to enhance the applicability of the network. In general, aircraft and cargo were defined in separate networks and are recovered using a sequential solving method. To explore the correlation between each research object and to complete each recovery action, the entity flow was defined to integrate different types of entities in the same network. To solve the problem of crew recovery, constraints such as crew duty and flight qualifications were added to the model, and a mixed integer linear programming model was constructed based on an improved flight network. This model can achieve integrated recovery of aircraft, cargo, and crew. To accurately evaluate the capacity constraints of the cargo aircraft, a unit load device was used to represent the volume of cargo and to improve the relevant models of capacity constraints. An entity aggregation approach was employed to reduce the number of entities to control the model complexity. The model evaluation was performed using operational data provided by a small freighter airline. The results show that the recovery solution causes a 42% reduction in the delay time. In the subsequent simulation experiments, six different disruption scenarios were established for two freighter airlines with multiple fleets. As the disruption rate increases, medium freighter airlines adopt the strategy of re-routing aircraft and rescheduling crew, while large freighter airlines focus on flight delays. The proposed integrated air cargo schedule recovery model based on an improved flight network can solve all the cases exactly in limited time, and the average error is 0.47%.