The planning of railway operations is a very complex process, in which timetables and other logistical plans need to be both reliable and robust to effectively prevent and cope with disturbances. However, research in the robustness of initial stabling plans, designed in an earlier planning phase, during the following planning phases, has been lacking, with the models created in research in the Train Unit Shunting Problem (TUSP) being generally deterministic in nature, even though stabling plans could quickly become infeasible when the stabling demand in the form of arriving and departing trains changes. This thesis therefore proposes a definition of the robustness of an initial stabling plan to changes in the stabling demand, such as changes in train lengths, as well as provide an assessment method of said robustness. The created Robustness Assessment Model (RAM) first generates an initial stabling demand and stabling plan, then performs a Monte Carlo simulation to generate a set of stabling plans created for variations of the initial stabling demand, based on changes in stabling demand such as train length. Finally, the RAM estimates the robustness of the initial stabling plan by analysing the differences between the initial and these generated stabling plan variations and how efficiently the initial plan is able to change to these plans to optimally facilitate the variations of the initial stabling demand. Running this model across three locations, each with three capacity utilisation scenarios, has shown that the model is able to estimate the robustness of an initial stabling with acceptable confidence, and furthermore is able to give insight into how capable the stabling plan creation method is in generating a robust solution. Furthermore, the RAM can also be used to investigate patterns in stabling plans which could predict the robustness of said stabling plans. Current shortcomings to the RAM are its relatively long runtime, the simple stabling plan creation process used in the RAM, and that only one-sided stabling yards without servicing scheduling have been incorporated. Further research is therefore recommended for extending the RAM with other stabling yard layouts and the scheduling of services, as well as improve the stabling plan generation process to take more constraints into account.