Several classes of endophytic fungi have been recently identified that convert cellulosic biomass to a range of ketones and other oxygenated molecules, which are potentially viable as biofuels, but whose oxidation chemistry is not yet well understood. In this work, we present a predictive kinetics model describing the pyrolysis and oxidation of diisopropyl ketone (DIPK) that was generated automatically using the Reaction Mechanism Generator (RMG) software package. The model predictions are evaluated against three experiments that cover a range of temperatures, pressures, and oxygen concentrations: (1) Synchrotron photoionization mass spectrometry (PIMS) measurements of pyrolysis in the range 800–1340K at 30Torr and 760Torr; (2) Synchrotron PIMS measurements of laser photolytic Cl-initiated oxidation from 550K to 700K at 8Torr; and (3) Rapid-compression machine measurements of ignition delay between 591K and 720K near 10bar. Improvements made to the model parameters, particularly in the areas of hydrogen abstraction from the initial DIPK molecule and low-temperature peroxy chemistry, are discussed. Our ability to automatically generate this model and systematically improve its parameters without fitting to the experimental results demonstrates the usefulness of the predictive chemical kinetics paradigm.