An early-life reliability model is presented that allows wafer test information to be used to predict not only the total number of burn-in failures that occur for a given product, but also the time at which they occur during burn-in testing. The model is a novel extension of an experimentally verified yield-reliability model based on the fact that defects that cause early-life reliability (burn-in) failures are "smaller", more subtle versions of the defects that cause failures at wafer test. Consequently, knowledge of defect densities following wafer test (inferred from wafer probe failures) provides knowledge of the relative magnitude of early-life reliability defect densities. It is shown that this fact can be exploited to produce die with varying burn-in duration requirements. This is accomplished by sorting die into "bins" based on known reliability indicators. Presently, two such indicators are known: the local region yield of the die in question, and the number of repairs performed on the die in question. The early-life reliability model presented in this work will demonstrate that chips sorted based on these criterion have different fall-out or failure rate curves in burn-in. This information can be used to select optimal burn-in durations while maintaining outgoing product reliability.