A burgeoning body of literature in pediatric neuropsychological assessment suggests executive functioning is the foundation of many procedural learning skills as mediated by cerebellar processing. Given the neuropsychological necessity of intact procedural learning ability for efficient academic learning, the accurate identification of what we have termed “procedural consolidation deficit” (PCD) may be an underpinning of mathematical learning disorder (MLD). Thus, one aim of the present study was to perform an exploratory correlational analysis between performance on pediatric neuropsychological tasks of procedural learning and a classification of MLD. The second aim was to utilize regression analysis of measures of procedural learning for predicting a clinically useful classification of MLD. Results revealed a significant correlation between performance on tasks of procedural learning and a classification of MLD. The follow-up regression model yielded the most predictive variables in identifying individuals with MLD, which included: (a) WISC-V Coding; (b) first administration of Trail Making Test Part B; (c) slope across five serial administrations of Trail Making Test Part B. The model was highly significant and had a classification accuracy for MLD of 87.4%. Results suggest performance on procedural learning tasks significantly predict a classification of MLD. Theoretical and clinical implications are discussed.