Soil Organic Carbon (SOC) has been identified as one of the major C sinks in the global carbon cycle, of which the exact size and spatial distribution are still difficult to determine quantitatively. Estimation of the amount of SOC present using remote sensing is mostly based on the overall decrease in reflectance in the solar reflective part of the electromagnetic spectrum. However, moisture content and soil roughness result in a comparable decrease, resulting in ambiguous identification of a specific soil type. Depending on the decomposition stage, SOC contains biochemical constituents like lignin and cellulose. Absorption features related to these constituents can be used to determine the SOC content of the soil. We investigated nine different soil types (n=40), originating from a wide range of climatic zones and a large variety in SOC content (0.06 – 45.1%). Spectral measurements of all soil samples were performed in a controlled laboratory environment. The ability of several spectral indices related to biochemical constituents’ detection towards the quantification of SOC were tested. Good relations were found for indices based on the visible part of the spectrum and for the absorption features related to cellulose. Cross validation was used to evaluate the predictive capacity of the spectral indices. The results demonstrate that it is feasible to use spectral indices derived from laboratory measurements to predict SOC in various soil types. The results allow establishing a perspective towards spatial distributed mapping of SOC using imaging spectroscopy.