BloomingLeaf is a web-based tool for modeling and analyzing goal models, which assists stakeholders in decision-making processes involving multiple actors with potentially evolving or conflicting intentions. BloomingLeaf allows users to analyze models multiple times using a variety of different configurations; however, prior versions did not include the ability to store analysis configurations or associate analysis results with those configurations. Our team led a major refactor of the existing code base to allow users to create and store multiple analysis configurations and associated results. These new model management features allow users to return to previous configurations, run analysis multiple times for a specific configuration, and save configurations and their results for distribution or future use. We expect these features to improve the ability of users to compare different analysis results and configurations, as well as collaborate on model analysis with other users. In turn, by improving the usability of BloomingLeaf, users can make more informed decisions from the analysis of their models. A poster deriving from Special Studies and STRIDE with Dr. Alicia M. Grubb, Assistant Professor of Computer Science.