<p>The quantitative assessment of volcanic unrest is essential for understanding volcanic processes and supporting decision-making. However, systematic approaches to evaluating unrest episodes remain underdeveloped, particularly during non-eruptive periods. The Volcanic Unrest Index (VUI), originally proposed in New Zealand as a communication tool, condenses diverse monitoring parameters into a single numerical index ranging from 0 to 4, with VUI 4 indicating the highest unrest level. Here we present the first application of the VUI to Japanese volcanoes, focusing on Mount Tokachidake and Mount Meakandake in Hokkaido, and develop an operational framework for its implementation using long-term monitoring datasets. Daily VUI values were constructed from monitoring datasets provided mainly by the Japan Meteorological Agency (JMA). For each data record, scores were assigned using thresholds defined based on proportion-based distributions of assigned scores or, where not applicable, from geophysical or geochemical thresholds. These daily scores were then aggregated into overall VUI values using a hierarchical framework, enabling daily evaluation through a sliding time-window approach across datasets spanning 50&#xa0;years. The VUI captured episodes of heightened activity associated with eruptions and non-eruptive unrest. At Tokachidake, the VUI exhibited peaks corresponding to the 1985 phreatic eruption, the 1988–1989 magmatic eruption, and the 2004 phreatic event, and reflected prolonged fumarolic activity after 2018. At Meakandake, VUI 4 emerged four times over the study period. Three of these corresponded to the eruptive periods in 1988, 2006, and 2008. Meanwhile, two other eruptions in 1996 and 1998 were not associated with VUI 4, but were instead categorized as VUI 3 and 2, respectively. Integration of multiple parameters reduced responsiveness relative to individual datasets. These results highlight the effectiveness of the proposed framework in providing a consistent, quantitative basis for comparing volcanic activity over multi-decadal timescales, while also underscoring limitations stemming from data availability and averaging across Categories. The study demonstrates that the VUI can serve not only as a framework for systematic evaluation of volcanic unrest in Japan but also as a computational platform for organizing and analyzing sub-eruptive activity, supporting future probabilistic eruption forecasting. Future directions include optimization of evaluation criteria across different volcanic settings and real-time automation.</p> Graphical Abstract <p></p>