Despite progress in developing methods to simulate or empirically predict other functional properties, contemporary stability characterization is overwhelmingly done experimentally via empirical make-and-break testing. Although this can reliably characterize a particular material, it is costly in terms of time and material and crucially only delivers information at the end of the design process. Even when such testing is done, generating mechanistic information requires additional analytical monitoring such as differential scanning calorimetry, thermogravimetric analysis, spectroscopy (XRD, XPS, IR, UV-Vis, NMR), mass spectrometry, cyclic voltammetry, or highpressure liquid chromatography amongst others. To the extent that stability properties are considered during design, it is typically only indirectly by limiting the scope of materials to established chemistries with known stability or by accounting for a small number of acute susceptibilities that are domain specific. Computational contributions at the design stage are primarily through thermodynamic energy estimates. Although this is a reasonable starting point, these say nothing about the kinetics and susceptibility of a material to degradation via specific stressors. Famously, diamond is thermodynamically unstable relative to graphite, but thermal decomposition is not kinetically favorable except under temperatures higher than 2000K. Recent advances in reaction prediction create the possibility that first-principles reaction data might provide a basis for estimating the degradation kinetics of prospective chemistries. Automatic reaction network exploration and transition state characterization algorithms have become more efficient and accurate. Although such characterizations still remain too expensive to be used in high-throughput applications for virtual screening and comparative down selection of prospective materials, they can potentially serve as the basis for generating kinetic data relevant to broad classes of degradation reactions. Critically, materials stability is mainly determined by the kinetics of the first irreversible degradation reaction and thus does not necessarily require a full elaboration of a many-step degradation network. Thus although data scarcity is no longer a fundamental obstacle, it remains to convert this information into a form that generalizes to similar chemistries to avoid the direct simulation of every new material.