In this paper we reflect on the effectiveness of cognitive mapping (CMing) as a method to study farm functioning in its complexity and its diverse forms in the framework of our own experiment with a diverse group of Flemish beef farmers. With a structured direct elicitation method we gathered 30 CMs. We analyzed the content of these maps both qualitatively and quantitatively. The central role of the concept “Income†in most maps indicated a shared concern for economic security. Further, the CMs indicated that farmers dealt with this shared social reality differently, as the relationships included in their maps referred to different functional processes relating to revenue streams, marketing strategies, investment decisions, dependence on production inputs, on-farm resource management, and personal well-being. With a clustering algorithm we grouped farmers based on the relationships in their maps, which allowed us to trace some of the broader patterns within the data, such as the existence of more business- and investment-minded farmers, in contrast to farmers focused on their quality of life, and animal production-oriented in contrast to marketing-oriented farmers. Taking into account farmers’ comments, we find that the applied methods had limited capability to classify farmers based on their perspectives on farming. Still, the system presentations proved useful to study what aspects farmers were working on or towards, and how these aspects may actually fit together as a whole. CMing was therefore mostly effective in exploring farm functioning in its complexity, and less so in exploring farm functioning in its diversity.