As robustness of social science is getting more attention, analytical choices have been found to be more important than previously thought. This thesis investigates robustness of intergenerational educational mobility estimates using multiverse analysis, a technique for incorporating many analyses into one framework while varying analytical choices such as variable coding, mobility measures, and exclusion criteria. Using ESS data from 16 European countries over nine survey rounds, results show substantial variation in point estimates, which in turn creates high variation in rankings of European countries. The conclusion is that analytical choices play an important role in calculating educational mobility estimates, and that ranking of European countries according to intergenerational mobility estimates is sensitive to varying these choices. Future mobility research should take this into account.