During operation aircraft brakes degrade due to wear. This degradation can be continuously monitored using brake degradation sensors. Using this monitored degradation data the remaining useful life of the brakes can be estimated by means of a prognostic model based on a Gamma probability distribution. Using the remaining useful life estimations a maintenance schedule can be optimized for a fleet of aircraft each fitted with multiple brakes accounting for maintenance constraints. Considered maintenance constraints include the availability of the maintenance hangar and the aircraft flight schedules. Because the problem contains multi-unit systems opportunistic maintenance can be applied, specifically economic dependance between components is considered in the optimization. Using a rolling horizon approach a long-term maintenance schedule can be created and evaluated. This long-term schedule is simulated using Monte Carlo simulation to achieve robust results on which meaningful conclusions can be drawn. To compare the results of the condition-based maintenance strategy a time-based maintenance strategy with fixed replacement intervals is used. It has been shown that the application of a condition-based maintenance strategy which makes use of prognostics can significantly improve the scheduling performance.