In previous work, we have shown that a first order plus logistic (FLOG) model can describe CO2 evolution from soil incubation studies with organic amendments. The FLOG model separates CO2 evolution into a first order exponential and a logistic pool that are separated in time. We proposed that the first order pool represents highly labile carbon while the logistic pool represents a complex form that is acted on by depolymerizing enzymes before mineralization. Given that the depolymerization of complex substrates has also been recognized as a likely rate-limiting step in nitrogen mineralization, and that soil nitrogen transformations under aerobic conditions are performed by organisms that respire CO2, we propose using the time-separated CO2 pools to describe soil mineral nitrogen (SMN) dynamics. In this approach, CO2 evolution curves are fit with the FLOG model using nonlinear regression (FLOG-C), and the predicted values from each CO2 pool are used to fit SMN curves by multiple linear regression (FLOG-N). We assume that nitrogen can either be mineralized or immobilized according to microbial demand during the decomposition of both the labile and polymerized pools. This approach was tested using data from an aerobic soil incubation with biosolids, and then applied to C and N datasets extracted from literature sources. We could successfully model complex soil mineral nitrogen dynamics of different shapes and from a variety of plant-based soil amendments using this approach.