<p>Knowledge transfer among New Product Development (NPD) projects is beneficial for reducing project duration and promoting technological innovation. To support effective knowledge transfer, we propose a clustering method for NPD projects based on similarity, integrating both structural and attribute similarities. First, to measure project structural similarity, we analyze both direct and indirect knowledge transfer relationships among project activities using the dependency structure matrix (DSM). Second, we measure project attribute similarity by calculating knowledge increments derived from sequential and iterative development processes. Finally, we apply a hierarchical clustering method to group similar projects, forming different programs. An industrial example is provided to demonstrate the proposed model. The results show that clustering projects into programs can enhance multi-project management by reducing coordination time for knowledge transfer within each program. Additionally, this approach provides some new insights, including quantifying project similarity based on knowledge transfer and understanding the influence of structural and attribute similarities on multi-project management.</p>