Despite the emergence of many new mobility options in cities around the world, fixed-route transit, such as bus travel, is still the most efficient means of mass transport. Since 2007, travel speed reductions and increased congestion due to greater mobility options competing for road space have led to a vicious cycle of ridership reduction and further increased congestion as former bus passengers take to other less efficient modes—bus ridership in Brooklyn has declined by 21% during this period. Intervention is required to promote a virtuous cycle and make the bus more competitive, especially in the face of increased competition from ride-hail services. This can be accomplished by redesigning the bus network in a way that does not increase operating costs while reducing user costs and increasing accessibility for more riders. In this webinar, Professor Joseph Chow and Ziyi Ma discussed their development of a new tool that allows transit agencies to design bus transit networks. By using multi-agent simulation, users can take a set of routes and output a GTFS file that includes a bus schedule with forecasts of ridership and load profiles, fare revenue and farebox recovery ratio (the share of operating expenses met by passenger fares), and operating cost. Through this technique, Professor Chow and Ziyi showed how an optimized bus schedule might improve the farebox recovery ratio up to 60% over the existing case.