Unplanned disruptions of rail transit networks have been studied extensively. Planned disruptions for works essentially are different mainly because of their longer duration, which allows passengers to build alternative route choice strategies. The literature on this topic remains scarce. In this study, a novel methodology was proposed to enable operators to evaluate different disruption management schemes and to obtain explicit estimations of travel times, passenger comfort flows, and levels of service. Statistical tools were used to evaluate the different strategies. The methodology is illustrated here through a large-scale application to a real line disruption in Paris. The disruption took place in July 2015 as the result of network maintenance work and affected Line A of Réseau Express Régional, a major suburban railway line that provides more than 1 million trips on a typical working day. Study results indicated that the disruption would have significantly increased the generalized cost (GC) of passengers if no action had been taken. The operator's disruption management scheme included bus bridging and increases in service frequency on alternative routes. Evaluation showed that this plan restored the average GC across the whole network. Passengers who initially used the disrupted line experienced increased GC when they used the longer, alternative routes. Passengers who initially used those alternative routes experienced lower GC as a result of the increase in service frequency. Finally, capacity problems were observed on the buses that ensured a bridge across the disrupted link.