<p>Early prediction of yield and its related traits in rice is important for successful raising of the crop. A study was planned (i) to elucidate the relationship between morphological and biomass traits and green part area rate per plant (GAP) at rice tillering stage, and (ii) to examine the potential for predicting yield-related traits using GAP. Apart from a relative index, GAP is also a green leaf area-related parameter, extracted from side-view 2-dimensional image captured from individual plant at tillering stage, using image analysis software developed with Fuzzy C-means clustering algorithm. Simple, multiple and standard regression analyses were performed to elucidate relationship among GAP and quantitative traits at tillering stage, and panicle mass per plant (PMP) and yield-related traits, respectively. The rate of contribution of GAP and yield-related traits to PMP was 42.1% for the number of panicles per plant (NPP), 35.5% for GAP, 21.5% for number of grains per panicle (NGP) and 0.9% for 1000 grain mass (1000 GM), respectively. Linear regression models showed a close relationships between PMP, NPP, NGP and GAP with determination coefficients (<i>R</i>²) of 0.8145, 0.7369 and 0.6887, respectively. In addition, GAP revealed poor relationship with 1000 GM (<i>R</i>² = 0.261). The findings of this study suggest that this methodology has a potential to predict yield and its related traits using GAP which can also used in selection process of rice breeding programs for developing high yielding varieties.</p>