After discovering low-energy clusters with the genetic algorithm, we filled gaps on the database (i.e., elements and sizes where no clusters were available) using the correlations among the energies of the elements. For a gap of a given element and size, we identified the most correlated element and used its 5 lowest-energy clusters of the same size as templates to generate new clusters that were likely to have low energy. We followed the process of re-scaling the interatomic distances using the bulk nearest-neighbor bond length.