The maintenance of a railway network is a complex process that is associated with high costs. The main causes for regular maintenance measures are profile wear and rolling contact fatigue (RCF). To help in this planning, state-of-the-art models of the use extensive multi-body simulations (MBD) to consider the influence of the vehicle fleet. This is very time-consuming as the complexity of the proposed models and the related degrees of freedom seem endless. Still, they have difficulties in predicting results from the real operations. In this paper, a hybrid approach is presented. The main objective is to use as few as possible MBD simulations to scale the wear, measured for one scenario (e.g. curve radius, vehicle fleet), and then apply it to a different scenario. The same MBD simulation results are also used as input for RCF prediction, i.e. crack initiation. This calculation is even more time consuming than the MBD simulations, since it requires a new simulation for each combination of vehicle types on each track section. This information is rarely known and often requires time-consuming parameter studies. Therefore, a new methodology is proposed, which calculates the crack initiation for each vehicle types separately. The results are then combined in post-processing for the whole vehicle fleet on the selected track section. This makes it possible to predict wear and RCF not only section-wise but on a whole network with acceptable effort.