Guaranteeing Feasible Outcomes in Judgment Aggregation Rachael H. Colley Abstract: In this thesis, we identify properties which guarantee consistent outcomes in a model of judgment aggregation, called 'binary aggregation with rationality and feasibility constraints'. We consider an outcome to be consistent when we can guarantee that the outcome will abide by with the feasibility constraint when all voters provide a judgment that is consistent with the rationality constraint. In order to guarantee feasible outcomes, we take inspiration from the formula-based model of judgment aggregation and translate both properties and the consistency results which follow from them, to our model. We translate types of 'agenda properties' and 'domain restrictions' to our setting, in particular the (k-)median property and value restriction, respectively. Following this, we recreate the corresponding consistency results, guaranteeing feasible outcomes on rational profiles. In turn, we study the computational complexity of problems related to the median property and value restriction, as well as their binary aggregation counterparts. Our results support the claim that they are complete for a class at least as hard as co-NP, and no harder than Π^p_2.