This study investigated six statistical merit school selection methods using student scores on a nationally normed, standardized achievement test to identify merit schools. More specifically, its purpose was to select a method for the Palm Beach County School system which meets the Florida merit school program criterion of fairness in terms of socioeconomic status (SES). Stanford Achievement Test (SAT) 7 Reading Comprehension and Total Mathematics scores for grades 3, 4, and 5 were used in the elementary school analysis, and score for grades 7 and 8 in the middle/junior high school analysis. The methods of analysis investigated were (1) student-based regression; (2) school-based regression; (3) school-based multiple regression predicting mean gain with free lunch; (4) disaggregated percentile groups; (5) adjusting school mean scaled score gains by the differential performance of free and non-free lunch students; and (6) unadjusted mean scaled score gains. Four aggregation techniques combining indices across grades and subtests to yield a single school merit index (SMI) were presented and three methods of setting cutoff points were suggested. Results indicate that none of these merit school selection methods can be highly recommended. School-based regression analysis appeared the most acceptable for large school districts. Further research is recommended. (BS)