An airplane model is usually obtained from preliminary wind tunnel experiments and CFD analysis. These models are then tuned from flight test measurements using system identification, and are used for airplane stability assessment and control design. However, sometimes no or little preliminary data and documentation are available and flight test identification is the main mean to obtain the model needed for control system design. If so, the purpose of this paper is to identify the grey-box model of an airplane without initial data using a combination of the least square and output error estimation methods. A grey-box model identification is preferred because it gives aerodynamic parameter estimations of the airplane. Before flight test data are available, this method was applied to the Cessna Citation X business airplane's high fidelity simulations and carried out with human-in-the-loop on a professional level D flight dynamics simulator designed and manufactured by CAE Inc. More than 1,000 flight simulations were made for different airplane configurations in speeds (140 to 240 kt), altitudes (10,000 to 46,300 ft), masses (24,000 to 33,000 lb) and longitudinal center of gravity positions (17 to 34% of the mean aerodynamic chord). Promising results were obtained for the short period dynamic motion, which allowed the Cessna Citation X's longitudinal stability assessment. The identification method that was used and tested on the research simulator will be used for Hydra Technologies S4 Ehéctatl UAV model identification from real flight test data.