Global nitric oxide (NO) emissions into the atmosphere are projected to increase in the coming years with the increased use of synthetic nitrogen fertilizers and fossil fuel combustion. Here; a statistical model (NO_STAT) is developed for characterizing atmospheric NO emissions from agricultural soil sources; and compared to the performance of other global and regional NO models (e.g., EDGAR and U.S. EPA). The statistical model was developed by developing a multiple linear regression between NO emission and the physicochemical variables. The model was evaluated for 2012 NO emissions. The results indicate that, in comparison to other data sets; the model provides a lower global NO estimate by 59%, (NO_STAT: 0.67 Tg N yr-1; EDGAR: 1.62 Tg N yr-1). We also performed a region-based analysis (U.S., India; and China) using the NO_STAT model. For the U.S., our model produces an estimate that is 47% lower in comparison to EDGAR. Meanwhile; the NO_STAT model estimate for India shows NO emissions 75% lower when compared to other data sets. A lower estimate is also seen for China; where the model estimates NO emissions 82% lower than other data sets. The difference in the global estimates is attributed to the lower estimates in major agricultural countries like China and India. The statistical model captures the spatial distribution of global NO emissions by utilizing a more simplified approach than those used previously. Moreover; the NO_STAT model provides an opportunity to predict future NO emissions in a changing world.