The aromatic region of two-dimensional heteronuclear 1H, 13C NMR spectra of natural organic matter and related materials (e.g., 1H and 13C chemical shifts ranging from approximately 5 to 10 and 80 to 140 ppm, respectively) is highly complex and difficult to interpret using conventional approaches. In principle, this region of the NMR spectrum should be amenable to detailed analysis, because the effects of many common substituents on the chemical shifts of aromatic carbon and hydrogen are well documented. This paper describes the development of a model for prediction of substitution patterns in aromatic rings by increment analysis (SPARIA). In the forward mode, SPARIA is used to predict the chemical shifts of 1H and 13C on aromatic moieties containing every possible combination of eight common substituents that are likely to be representative of substituents on aromatic moieties in natural organic matter. The accuracy of SPARIA in the forward mode is evaluated for 29 aromatic compounds (100 peaks) by comparison of predicted chemical shifts for 1H and 13C with experimental values and with predictions of commercially available software for prediction of NMR spectra. The most important development in this paper is the inverse mode that is built into SPARIA. Given chemical shifts for 1H and 13C (such as may be obtained from a two-dimensional, heteronuclear NMR spectrum), the inverse mode of SPARIA calculates all possible combinations of the eight selected substituents that yield chemical shifts within a specified window of chemical shift for both 1H and 13C. Both the distribution of possible substitution patterns and simple descriptive statistics of the distribution are thus obtained. The inverse mode of SPARIA has been tested on the 29 aromatic compounds (100 peaks) that were used to evaluate its forward mode, and the dependence of the inverse process on the size of the chemical shift window has been evaluated. Finally, the inverse mode of SPARIA has been applied to selected peaks from the two-dimensional heteronuclear HSQC spectrum of a sample of natural organic matter that was isolated by reverse osmosis from the Suwannee River in southeastern Georgia.