We employed a regionalization algorithm called regionalization with dynamically constrained agglomerative clustering and partitioning (REDCAP) to analyze the Body Mass Index (BMI) of school students in Texas and its association with social economic status (SES). The study includes 741 school districts in Texas. BMI data were extracted from the Physical Fitness Assessment Initiative program managed by Texas Education Agency. SES was described using six variables that cover two aspects, Household SES and Neighborhood SES. The study period was the 2012–2013 academic year. We used three REDCAP algorithms to delineate regions considering both spatial contiguity and attribute homogeneity. The result shows that Full-order-CLK algorithm of REDCAP is most effective in producing regions to delineate the patterns of Texas students’ BMI and its relationship with SES. Moreover, two- and six -class regions are the optimal numbers for such a regionalization. Our study reveals the regional patterns of school youth obesity in Texas when connecting to SES—particularly in regions with high rate of obesity and low SES, such as the regions in South and West Texas, and the three school districts in San Antonio. The findings can provide guidance for regionalized policy and practice to fight against school youth obesity in Texas.