This study focuses on the estimation of kharif paddy area using optical data from remote sensing, particularly during the early monsoon season when cloud-free data is more readily available. Remote sensing for crop monitoring has evolved significantly with the advent of modern satellites offering high spatial and temporal resolution. In the kharif season of 2019, Sentinel-2A optical data from the European Space Agency (ESA) was utilized at the peak flowering stage of paddy to estimate the crop area in Tamil Nadu. The study employed both supervised and unsupervised classification methods, with a preference for supervised classification due to prior knowledge of the study area. Training sites were developed using ground truth data collected during field surveys, leading to the classification of land into six categories: Paddy, Waterbody, Settlements, Barren lands, Other crops, and Miscellaneous. The Sentinel-2A data was then analyzed using the maximum likelihood classifier in ArcGIS software to delineate the paddy area, with iterative refinements and accuracy assessments ensuring reliable results. The final analysis revealed a total kharif paddy area of 22,246.01 hectares in the Thanjavur district. Detailed block-wise statistics were generated, showing Orathanadu block with the highest paddy area of 3,117.43 hectares and Budalur block with the least at 340.97 hectares. The findings highlight the effectiveness of using high-resolution satellite data and supervised classification methods for accurate crop area estimation with kappa index of 0.83.