This work aims to build different types of data-driven approaches in modeling European ATM Network Flow to capture the behavior of delay propagation over the network. To build proper network models and set their parameters, we have utilized historical flight track data, which includes last filed flight plans and actual movements. Through their comparisons, actual delay profiles of the airports and continental inflows/outflows were evaluated. In order to reduce the complexity of the models, most congested 103 European airports were held, and other airports were aggregated without considering their topological specs. Then, we have utilized these models to simulate the impact of local disturbances on the whole network through real air traffic data of certain days that disrupted due to capacity reductions issues such as heavy rain at an airport, an airline of controller strikes, runway construction, industrial events, etc. The results of these comparisons that performed by the certain simulations are reviewed to provide the performance assessment of the methods in demand-capacity balancing. (C) 2017 The Authors. Published by Elsevier B.V.