This paper proposes a methodological framework for diagnosing and strengthening collaboration within agroecology networks through the application of social network analysis (SNA). While civil society organizations are playing an increasingly central role in advancing agroecology, the internal dynamics that shape inter-organizational collaboration remain underexplored. This study employs SNA to visualize and quantify relational patterns among 25 member organizations of Participatory Ecological Land Use Management (PELUM) Uganda. Data was gathered through focus group discussions, semi-structured interviews, and document analysis, and were subsequently analyzed using Gephi for modularity-based network visualization and Kumu for ca\lculating centrality metrics. The analysis identified key actors (e.g., MOS6, MOS7, MOS17) with high centrality scores, suggesting their strategic roles in influencing, brokering, and disseminating information across the network. In contrast, peripheral organizations exhibited limited connectivity, revealing structural fragmentation and underutilized opportunities for collaboration. Validation sessions with network members confirmed the accuracy of the visualizations and provided critical insights into informal relationships and collaboration barriers. The study illustrates how SNA can uncover latent network dynamics and support the development of evidence-based strategies for building more coordinated, inclusive, and strategically aligned agroecology partnerships. The findings offer a practical diagnostic tool for networks aiming to scale agroecology through enhanced internal coordination, knowledge sharing, and collaborative learning.