Engine maintenance needs to be planned timely and strategically. This can only be done if the health of the engine can be predicted, which requires an accurate engine performance model. Developing such a model is becoming increasingly challenging, due to the reduced number of sensors in modern gas turbines. Besides this, a lot of data is proprietary and not available to the maintenance provider. This leads to the objective of the thesis: Improve Gas Path Analysis at KLM Engine Services, by developing a systematic approach for modelling modern turbofan engines using sensor measurements and general physical relations. For the on-design modelling general physical relations were used to bridge the gap caused by the reduced amount of data. The off-design modelling was done by scaling baseline maps from open literature using second order polynomials. The outcome was verified by developing two engine models in parallel and the validation was done using on-wing data.