The concept of an aircraft capable of both hover as well as fast forward flight (hybrid) has recently been implemented on unmanned aerial vehicles (UAV). Hybrid UAVs combine hover capability with long range and endurance. As UAVs are often required to operate without human intervention, there is a call for autonomous guidance of hybrid UAVs. Because the dynamics in the transition region from hover to forward flight are not well known, this research focusses on the development of a longitudinal model for a hybrid UAV based on test flight data. The same approach can be used for other types of airframes as well, allowing cheap and easy modelling. Sensors were logged for nine different flights and a Kalman filter was used for state estimation. The system was excited by doublet inputs on the commanded pitch and thrust. From the input-output response a piecewise linear model was estimated. This model was verified by comparing the measured doublet input response to the simulated response based on the model, yielding a very similar result.