National gifted standards recommend that educators select and use multiple assessments that measure diverse abilities, talents, and strengths. As such, gifted coordinators are faced with multiple data types (ability tests, achievement tests, teacher checklists) to analyze in their selection of students for gifted program identification. Considering best practices in gifted identification and using an identification matrix, learn how to normalize these multiple data types using student screening and selection procedures that are statistically accurate. Use of this identification matrix also simplifies the disaggregation of data, which can be used in the identification process of under-served gifted populations.