Knowledge networks in regional clusters are fundamental to support innovation and local development. Within clusters, family firms are key in creating business opportunities and supporting the establishment of inter-organizational networks. Yet, their role within regional clusters for knowledge transfers is still not well understood, especially in comparison with non-family firms. This paper applies Exponential Random Graph Models (ERGMs) to network data collected from the Parabiago cluster, one of the most important Italian footwear clusters, to contribute to a better understanding of the network strategies of family firms. We identify distinct network strategies associated with the cluster firms, accounting for different knowledge exchange types: technological, market, and managerial. In our modelling, we control for firm-level attributes and dyadic-level attributes, such as geographical distance and cognitive proximity between cluster firms. Our results suggest that the proneness of family firms to grow networks is highly robust relative to non-family firm relationships, irrespective of knowledge types being exchanged. Moreover, family firms tend to establish connections with other family firms, showing the presence of homophily in their networking approach; however, non-family firms are rather different, since they do not have the same homophilous approach when it comes to exchange knowledge with other non-family firms. These results indicate that the nature of ownership is driving knowledge exchange differences. This key feature of family-only relationships in clusters may help managers and policymakers in devising more effective and targeted cluster strategies.