As the profit margins of the airline industry are relatively low, it is of utmost importance to keep costs low in order for airlines to stay competitive. An important cost factor is maintenance costs, as it can take up around 10-20 % of the total direct operational costs. Currently, much development is taking place in developing condition-based maintenance (CBM) strategies. These strategies on the one hand leverage remaining useful life (RUL) predictions of components to enable better planning and lower repair costs while on the other hand less preventive maintenance tasks are required due to the increase of useful sensor data available. This paper develops insights in the potential benefits that CBM can have as a function of different prognostic performance levels. This is done by developing cost- benefit models which accept a wide range of parameters being able to simulate prognostic effectiveness on different aircraft fleets. Results are obtained by using real MRO and operator input data. The results show that CBM can be beneficial, given that the model has a sufficient specificity and the component supply chain scales accordingly.