This thesis project is focused on the practice of bus network redesigns in the United States between 2014 and 2023. After introducing the concept of bus network redesigns in Chapter I, in Chapter II I summarize the existing academic, historical, and gray literature on bus network redesigns. I observe that network redesigns are used to adapt transit networks to changes in urban development and travel patterns. I also find that academic literature on bus network redesigns has focused primarily on modeling their accessibility impacts, including for the ways redesigns can improve riders’ access to jobs and health care services. Following, I consider the robust gray literature on bus network redesigns, including writing on individual blogs, reports by advocacy groups, and policy case studies. I conclude that there has been no comprehensive study on the quantitative impacts of bus network redesigns, and also observe that much of the work being done to shape network redesigns comes from the professional, not academic side of the field. In Chapter III I summarize my key findings from a series of interviews conducted with active transit planners who have worked on bus network redesigns. Those planners observe that bus network redesigns distinguished themselves from existing transit planning methods in the mid-2010s. They also demonstrate how bus network redesigns are spread in a variety of ways, oftentimes proposed by one of a few prolific consulting firms, but also developed internally by transit agencies, or municipal governments. Finally, I detail the way that community engagement has become an increasingly robust component in bus network redesign projects, especially as redesigns have grown in scale. In Chapter IV, I establish a framework for measuring the effects of bus network redesigns that can be added to as more data becomes available for treated networks. I use National Transit Database data to measure changes in yearly ridership and vehicle operating hours at transit agencies. I cluster agencies with their peers using a k-means clustering technique and assess treatment effects via an OLS linear regression, first with time as a binary variable, then with time as a panel variable. I find no statistical differences between treated and untreated networks, although I do observe weak positive associations with operational performance metrics over time in treated networks. I also calculate difference in difference effects for treated networks from their peers. I find slight associations with operational efficiencies, albeit with large standard errors that suggest diverging trends among treated networks. To conclude the thesis, I suggest that, regardless of their quantitative effects, bus network redesigns are intrinsically valuable for transit agencies because of how they facilitate wholistic, network-scale thinking about how transit can serve our cities.