A decentralized, and sustainable sewer inspection plan at the city scale demands multiple inspection methods with different areas of impact. While sewer deterioration models offer great areas of impact, spatial mapping can assess the vulnerability of the system without prior knowledge of the pipe’s structural health condition. In this study, we assess and prioritize sewer deterioration factors such as pipe age, material, sewer type, node degree, flow velocity, and surface vegetation for vulnerability hotspot mapping of a sewer system in Dresden, Germany. The validation and sensitivity analyses revealed that flow velocity, pipe age, and surface vegetation are the most sensible factors to model, respectively. The linear model resulted in 76% efficiency and a mean squared error of 0.918 while it was improved with a random forest algorithm which points out vulnerability mapping potential as an early sewer inspection method at the city scale.