Stochastic actor-oriented models (SAOMs), introduced by Snijders (1996), are used for modeling dynamic social networks in which node-level characteristics play an important role in the structure of the network, such as friendship networks. These models are very complex and can be hard to conceptualize. To better understand the behavior of SAOMs, we utilize model visualization techniques introduced in Wickham et al (2015). SAOMs are a prime example of a set of models that can benefit greatly from application of model visualization. With the help of static and dynamic visualizations, we bring the hidden model fitting processes into the foreground, eventually leading to a better understanding and higher accessibility of SAOMs for social network analysts.