Visible (VIS) and near-infrared reflectance spectroscopy (NIRS) combined with multivariate data analysis was used to predict potentially mineralizable nitrogen (PMN) and nitrogen in particulate organic matter fractions (PSOM-N). Soil samples from a long-term experiment (n=24) as well as soils under commercial management (n=160) in Uruguay (South America) were analysed. Samples were scanned in a NIRS 6500 monochromator instrument by reflectance (400–2500 nm). Modified partial least square regression (MPLS) and cross validation were used to develop the calibration models between NIRS data and reference values. NIRS calibration models gave a coefficient of determination for the calibration (R2CAL)>0·80 and the standard deviation of reference data to standard error in cross validation (RPD) ratio ranging from 2 to 5·5 for the variables evaluated. The results obtained in the study showed that NIRS could have the potential to determine PMN and PSOM-N fractions in soils under different agronomic conditions. However, the relatively limited number of samples led us to be cautious in terms of conclusions and to extend the results of this work to similar conditions.