A common practice in biomarker discovery is to decide whether a large laboratory experiment should be carried out based on the results of a preliminary study on a small set of specimens. Consideration of the efficacy of this approach motivates the introduction of a probabilistic measure, for whether a classifier showing promising results in a small-sample preliminary study will perform similarly on a large independent sample. Given the error estimate from the preliminary study, if the probability of reproducible error is low, then there is really no purpose in substantially allocating more resources to a large follow-on study. Indeed, if the probability of the preliminary study providing likely reproducible results is small, then why even perform the preliminary study?