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Among community college leaders and others interested in reforms to improve student success, there is growing interest in adopting machine learning techniques to predict credential completion. However, a new working paper contends that machine learning algorithms are often complex and not readily accessible to practitioners, for whom a simpler set of near-term measures may serve as sufficient predictors.