Microorganisms play a pivotal role in industrial wastewater treatment, serving as a critical barrier to water purification and safeguarding human and environmental health. Despite their importance, the biogeographic distribution and assembly mechanisms of microbial communities in cold-rolling wastewater treatment systems remain poorly understood. This study analyzed 101 microbial samples from nine regions using high-throughput sequencing, revealing rich microbial diversity and distinct regional aggregation patterns. Random forest analysis identified key biomarkers, often low-abundance species, while a unique core microbial community was strongly correlated with pollutant removal efficiencies, including chemical oxygen demand (COD), total organic carbon (TOC), and total nitrogen (TN). Neutral community model analysis demonstrated that microbial community assembly is driven by both stochastic and deterministic processes. Co-occurrence network analysis further highlighted o__1-20 and g__Ellin6067 as pivotal taxa influencing community structure. Among environmental factors, nitrite nitrogen (NO₂-N) and COD were identified as critical drivers of community assembly. This study provides the first comprehensive characterization of microbial biogeographic patterns in cold-rolling wastewater treatment plants across China. The findings deepen our understanding of microbial diversity, distribution, and community dynamics in industrial wastewater systems, offering valuable insights for optimizing treatment processes.