Two quantitative enrollment projection techniques and the methods used by researchers at the Ohio Board of Regents (OBR) are discussed. Two quantitative approaches that are typically used for enrollment projections are curve-fitting techniques and causal models. Many state forecasters use curve-fitting techniques, a popular approach because only historical data are required. If enrollment trends are unstable, however, curve-fitting techniques are less useful and may be inappropriate. Causal models look at cause and effect relationships between independent factors and enrollment patterns. In Ohio, enrollment projection through 1992 for public higher education institutions is based on a dual approach. One, based on demographic information, is the Demographic Simulation of Ohio (DS), and the other, the Regents Enrollment Forecasting System (REFS), is based on high school graduate pools by county, matriculation rates, institutional market shares, and historical enrollment patterns in public postsecondary institutions in Ohio. A description of these methods and their advantages and disadvantages are provided. Comparison of full-time and part-time projections is also discussed. (SW)