This study proposes an analytical framework to quantitatively measure the degree of convergence in R&D projects using patent-based indicators. This framework uses patent data collected during the R&D planning stage to evaluate both technological convergence and cross-industry generality. First, patents related to each R&D project are identified, and technological concentration and convergence are measured using the International Patent Classification (IPC). Next, by applying the linkage table between the Korea Standard Industrial Classification (KSIC) and IPC provided by the Korean Intellectual Property Office (KIPO), the industrial classification of each project is determined, and its cross-industry generality level is assessed. The derived technological convergence and cross-industry generality values are mapped to the x- and y-axes, respectively, to visualize the convergence distribution across all projects, providing a comparative framework for analyzing the convergence characteristics among projects. This study moves beyond conventional qualitative approaches by enabling data-driven assessment and prediction of convergence levels at the R&D planning stage. Integrating this framework into the information systems managed by specialized R&D organizations can enhance convergence-oriented project management and promote more effective convergence research.