This thesis investigates how Marine recruit information available at entry can be used to predict which occupational field OCCFLD is best suited to an individual and if a Marine successfully completes the first term of enlistment. Multinomial regression models are developed to calculate estimated probabilities that a given recruit will attain United States Marine Corps USMC Computed Reenlistment Tiers I, II, III,or IV in a particular OCCFLD. Optimization of OCCFLD assignment based on the developed models illustrates the potential value of insight gained from recruit information available prior to enlistment. The relationship of recruit characteristics available prior to enlistment and the USMC Computed Tier Score assigned in the last year of a Marines first enlistment is dependent upon the OCCFLD assigned. We recommend identifying OCCFLDs with the highest estimated probabilities of Tier I or Tier II attainment at the recruitment phase. Providing recruits and recruiters a tool that provides estimated probabilities of attaining Tier I or Tier II in descending order for each OCCFLD during initial assignment has the potentialto increase the caliber of Marines across all OCCFLDs and to aid in assessing the current OCCFLD assignment practices.