This project investigated various visual structures for sets of business rules. The team developed software for transforming arbitrarily constructed decision trees into Oblivious read-Once Decision Graphs (OODGs) and Exception Directed Acyclic Graphs (EDAGs). The team then analyzed the visual complexity of the different structures to determine whether the OODGs and EDAGs are more human-readable than the original trees. This work will form the foundation for a potential EDAG visualization component for Fair Isaac’s Blaze Advisor system.