<p>Accurate assessment of agroforestry extent and its carbon sequestration potential is crucial for achieving India’s climate targets under the Paris Agreement. However, detailed region-specific estimates, particularly from the country’s diverse agro-climatic zones, remain scarce. Therefore, the present study evaluated the spatial extent and carbon sequestration potential of agroforestry systems in Kangra district, Himachal Pradesh, employing a synergistic approach integrating geospatial analysis with process-based carbon modelling. Various combinations of Sentinel-2 spectral bands, vegetation indices, and biophysical parameters were employed to delineate agroforestry and other land-use systems using the Random Forest algorithm. The findings indicated that agroforestry emerged as a dominant land use, covering 30.81% to 32.08% of the total area. The combination of Sentinel-2 and three biophysical parameters achieved the highest classification accuracy (79.77%) and kappa coefficient (0.743), providing the most reliable delineation of agroforestry areas. Moreover, the 25-year CO2FIX simulation projects an increase in tree biomass from 109.45 to 216.07&#xa0;Mg DM ha⁻¹ and carbon stock from 76.79 to 153.08&#xa0;Mg C ha⁻¹. Net carbon sequestration is projected at 76.29&#xa0;Mg C ha⁻¹, resulting in an annual sequestration rate of 3.05&#xa0;Mg C ha⁻¹&#xa0;yr⁻¹ and a district-level CO₂ mitigation potential of 2.07 Mt CO₂ yr⁻¹. Overall, the findings underscore the vital role of agroforestry in strengthening regional carbon sinks and guiding policymakers in integrating it into climate-resilient land management and mitigation strategies.</p>