In native mass spectrometry, it has been difficult to discriminate between specific bindings of a ligand to a multiprotein complex target from the nonspecific interactions. Here, we present a deconvolution model that consists of two levels of data reduction. At the first level, the apparent association binding constants are extracted from the measured intensities of the target/ligand complexes by varying ligand concentration. At the second level, two functional forms representing the specific and nonspecific binding events are fit to the apparent binding constants obtained from the first level of modeling. Using this approach, we found that a power-law distribution described nonspecific binding of α-amanitin to yeast RNA polymerase II. Moreover, treating the concentration of the multiprotein complex as a fitting parameter reduced the impact of inaccuracies in this experimental measurement on the apparent association constants. This model improves upon current methods for separating specific and nonspecific binding to large, multiprotein complexes in native mass spectrometry, by modeling nonspecific binding with a power-law function.