During clerical review for a match and merge solution, a data steward could face thousands of records that must be either merged or rejected. The Machine Learning Match Recommendations (MLMR) ease the workload by providing recommendations for merging or rejecting based on the data steward's previous decisions. This functionality works entirely on the Clerical Review Task List and does not influence the matching algorithm. When using the recommendations combined with the filtering and merge / reject bulk update capabilities, the data steward can resolve the task list more rapidly.