MPLS recovery mechanisms are increasing in popularity because they can guarantee fast restoration and high QoS assurance. Their main advantage is that their backup paths are established in advance, before a failure event takes place. Most research on the establishment of primary and backup paths has focused on minimizing the added capacity required by the backup paths in the network. However, this so-called Spare Capacity Allocation (SCA) metric is less practical for network operators who have a fixed capacitated network and want to maximize their revenues. In this paper, we present a comprehensive study on restorable throughput maximization in MPLS networks. We present the first polynomial-time algorithms for the splittable version of the problem. For the unsplittable version, we provide a lower bound for the approximation ratio and propose an approximation algorithm with an almost identical bound. We present an efficient heuristic which is shown to have excellent performance. One of our most important conclusions is that when one seeks to maximize revenue, local recovery should be the recovery scheme of choice.