Railway switches and crossings or turnouts are integral infrastructure demands of a railway network. They connect different tracks enabling flexible train operations. When the train passes the turnout, discontinuities in the rail profile, gaps in the surface, varying stiffness, and sudden direction changes induce elevated dynamic forces and relative sliding. The increase in the rolling-sliding contact load involves higher degradation and failure rates compared to the regular track. The main driving mechanisms of the degradation process are wear and rolling contact fatigue (RCF). Strain accumulation and profile adaptions due to plastic deformation additionally affect both failure modes. The higher failure risk results in disproportional costs for maintenance and replacement. To maintain availability and safety as well as to reduce costs predictive models for long-term damage assessment have gained importance. The present work introduces a new modular software-assisted tool to simultaneously quantify the wear and RCF degradation of turnout components. The proposed damage assessment framework works on the contact patch level to bridge the length scale gap between global vehicle-track interactions and local damage processes. The software can process load inputs originating either from numerical simulation models, from the user or from track measurements. The implemented prediction models, for now, incorporate standard wear and RCF models from literature as well as an advanced crack application. The latter uses an advanced crack model to predict the growth of surface-initiated cracks such as head checks. As the numerical predictions from damage models strongly depend on the quality of material data, wear tests on a twin-disc machine are conducted for the investigated rail steels. A new mode-II fatigue crack growth experiment and a method to produce high-pressure torsion processed tubular specimens is developed. With this new experimental set-up, the crack growth resistance can be measured under mode-II loading in a severely deformed microstructure. The results are required for example in the crack application to account for mixed-mode crack propagation. The present work applies the material assessment tool in combination with tailored vehicle-track models considering advanced elastic-plastic material models to evaluate the wear and RCF behavior of crossing components. At first, the wear and RCF damage of a manganese steel crossing nose is investigated including a verification and validation of the assessment framework with literature data and field measurements, respectively. Furthermore, a numerical framework to assess the performance of two different switch rail materials is presented. Finally, different material concepts for the frog of the turnout are compared regarding their failure mode. In conclusion, these case studies prove that the proposed software is a useful tool to analyze the long-term wear and RCF behavior of railway components.