The paper focuses on a validation study for a macro-cognitive model of mental workload of airport traffic controllers (ATCOs). This model constitutes a means for quantifying and analysing the distribution of ATCOs workload over time dependent on different traffic scenarios. Workload is modelled via the amount of chunks in working memory. In a one-factor experimental Simulator-Study workload ratings were gathered with different traffic load, using a modified RSME scale within and NASA-TLX after each scenario. The data are analysed and discussed concerning the successful experimental manipulation and the estimation of goodness of fit of the model and experimental data. Therefore the average workload ratings of the participant and the model within each scenario as well as the distribution of workload over time for each participant-model pair are compared. The developed model can serve as a tool for the design of adaptive automation and supporting systems and can help to better understand workload dynamics of airport traffic controllers.