Actuarial recidivism risk tools such as COMPAS assess individuals across dozens of independent 1D dimensions; current implementations index these scores sequentially, precluding efficient multidimensional similarity search. Morton encoding of composite risk profiles via bit-interleaving would preserve conceptual neighborhood proximity, enabling rapid case-based reasoning across large offender databases without high-dimensional distance calculations — an approach not yet investigated in the criminal justice data science literature.