Abstract: Characterization of microstructure and grain boundary character distribution (GBCD) during iterative thermo-mechanical processing (TMP) of 316L stainless steel were done using electron backscatter diffraction (EBSD). Results from EBSD scans were analyzed in terms of the fraction of special boundaries, their deviation from ideal misorientation, connectivity of random high-angle grain boundaries, and grain size. In order to understand the efficacy of the iterative processing route leading to a well-connected twin boundary network, additional analysis was done in terms of twin-related domain statistics and triple junction distribution. Results from these analyses show that initial iteration results in a microstructure with insufficient twin boundary density, and a poor twin boundary network. Although the next iteration leads to a small increase in twin statistics, it also does not significantly improve the statistics of favorable grain boundaries and their network. However, the fourth iteration of the processing results in a large improvement in both the population and distribution of favorable grain boundaries. All the subsequent iterations were found to result in microstructural deterioration in terms of both population and network of these grain boundaries. Based on the analysis, role of underlying mechanisms such as strain-induced grain boundary migration and static recrystallization in the effective optimization of GBCD was analyzed. The present research gives important insights into these mechanisms and their control during TMP in order to achieve an engineered microstructure. Graphic abstract: [Figure not available: see fulltext.]. © 2020, Springer Science+Business Media, LLC, part of Springer Nature.