From 2019 onwards, airline pilots will be required to follow stall training in simulators. A major open research question is which level of model fidelity is required for effective training. As part of an effort to answer this question, a stall model of a Cessna Citation II aircraft is developed from specifically-gathered flight test data. The model is based on Kirchoff’s theory of flow separation. During identification, the nonlinear and linear parameters of the model are estimated in separate steps. This distinction enables the application of a semi-objective model structure selection method using multivariate orthogonal functions. It is shown that stall-related effects should be included in the model equations for lift, drag, and pitch moment. The model parameters are accurately estimated, and model output is validated around a flight condition of 5,500 m altitude. The developed methodology is concluded to be well-suited for stall model identification of small business jets.