Visible and near-infrared reflectance spectroscopy (VNIRS) is a rapid and non-destructive proximal sensing method that can predict various soil properties, and has the potential to dramatically reduce the time and cost of soil analysis. In this study, the predictability of VNIRS was assessed for sixteen soil quality indicators of Western Kenyan soils. It successfully predicted SQ indicators (R2 > 0.80; ratio of performance to deviation (RPD) > 2.00) including Ca, soil organic matter, active carbon, water content at permanent wilting point, cation exchange capacity, clay, sand, and Cu of Western Kenyan soil. VNIRS was also employed to analyze soil organic carbon (SOC) distribution within a microwatershed in Costa Rica. It successfully predicted SOC content with R2 of 0.82. It appears that high spatial sampling intensities, inexpensive SOC analysis, and the "measure and multiply" extrapolation method provided by VNIRS is highly applicable for studying SOC distribution in complex agroforestry watershed.