As aircraft maintenance is transitioning towards data- driven condition-based maintenance (CBM), its cost and performance objectives need to be re-evaluated: how are these objectives related under various CBM strategies?; which objectives are conflicting?; what are the trade-offs between the conflicting objectives?; what is the impact of this transition on aircraft maintenance? We propose a methodology based on discrete-event simulation to analyze CBM of aircraft from the perspective of multiple objectives. The simulation considers an aircraft operations model, systems of multiple, redundant aircraft components, stochastic degradation models for components, and specific CBM strategies. In particular, we analyze two CBM strategies for component replacement, which are based on sensor monitoring and remaining-useful-life prognostics. As objectives for these strategies, we consider the minimization of the number of component replacements, the number of unscheduled replacements, the number of degradation incidents, the delay caused by maintenance, and the mean number of flight cycles to replacements (MCTR). We identify the main conflicting objectives and generate Pareto fronts. We show non-trivial trade-offs between the performance-oriented objectives (the number of degradation incidents and the delay due to maintenance) and cost-oriented objectives (MCTR). In fact, the CBM strategy based on remaining-useful-life prognostics dominates the other strategies in the knee region of the Pareto fronts. This implies that the transition towards data-driven CBM strategies can reduce the cost while maintaining the performance. Moreover, the proposed methodology is readily applicable to analyze general aircraft systems and other maintenance strategies.