Quantitative data seems to be essential when validating social agent-based models. However, data collection can be challenging for explanatory social agent-based simulations due to the inherent complexity of underlying social processes. Despite repeated mentions of validating such ABM’s qualitatively, we observed an absence of explicit approaches. In this paper, we propose the use of qualitative structural validation, combining several validity methods. We will demonstrate its application on our own ABM about identity fusion (van den Hurk et al. in Exploring the Stepwise Process and Consequences of Identity Fusion in Different Groups: An ABM. Conference of the European Social Simulation Association. Springer Nature Switzerland, Cham [17]) and argue how a qualitative approach can create explainable stories, contributing to exploration and explanation of social phenomena.