This article is concerned with developing a measure of general academic ability (GAA) for high school graduates who apply to colleges, as well as with the identification of optimal weights of the GAA indicators in a linear combination that yields a composite score with maximal reliability and maximal predictive validity, employing the framework of the popular latent variable modeling methodology. The approach to achieving this goal is illustrated with data for 6,640 students with major in Science and 3,388 students with major in Art from colleges in Saudi Arabia. The indicators (observed measures) of the targeted GAA construct were selected from assessments that include the students' high school grade and their scores on two standardized tests developed by the National Center for Assessment in Higher Education in Saudi Arabia, General Aptitude Test (GAT) and Standardized Achievement Admission Test (SAAT). A unidimensional measure of GAA was developed initially, with different sets of indicators for colleges with major in Science and for colleges with major in Art. Appropriate indicators for colleges with major in Science were the high school grade, total score on GAT, and four SAAT subscales on Biology, Chemistry, Physics, and Math. With respect to colleges with major in Art, appropriate GAA indicators were the students' high school grade and their scores on GAT-Verbal, GAT-Quantitative, and SAAT. Although the case study is Saudi Arabia, the methods and procedures discussed in this article have broader utility and can be used in different contexts of educational and psychological assessment.