Objective: Mass shootings in the United States have received significant attention from the media and scholars alike. Recent work indicates that mass shootings are becoming more deadly in the United States, making the identification of critical warning signs among would-be mass shooters of paramount importance. Method: To this end, we applied a regimen of psychometric network analyses to a dataset of crises observed among mass shooters (N = 177; M age = 34.26, SD age = 12.31; 98.31% male) from the United States prior to their attacks. We also conducted a regression and subsequent dominance analysis using these crisis indicators as covariates of shooting severity to identify which shared the most variability with shooting severity. Results: First, our exploratory graph analysis identified two specific groupings of crises: Distressed Isolation and Disturbed Affect. Next, our network analysis revealed that agitation was a highly important node due to the strong links it shared with mood instability and abusive behaviors. However, isolation yielded the greatest community cross-loading and the most edges in the network. We also found that depression and mood instability were the strongest correlates of shooting severity, as they shared the greatest amount of variability with shooting severity. Conclusion: We argue that social isolation is an ideal candidate for the acquaintances and communities of would-be shooters to intervene. Our findings are discussed within the framework of the path to intended violence model.