Log prices can vary significantly by grade: grade 1 logs are often several times the price per unit of grade 3 logs. Because tree grading rules derive from log grading rules, a model that predicts tree grades based on tree and stand-level variables might be useful for predicting stand values. The model could then assist in the modeling of timber supply and in economic optimization. Grade models are estimated for ten species groups found in the southern Appalachians, using data from several thousand trees and permanent plots in the USDA Forest Service's Forest Inventory and Analysis (FIA) database. The models correctly predicted grades of a majority of trees in both a test and a validation data set, and predictions of grade proportions across a sample of the population were usually within three percentage points of actual grade proportions. But success of models varied across species and diameter groups. Considering several measures of modeling success, the most accurate models were those predicting tree grades for softwoods and larger hardwoods. For. Sci. 44(1):73-86.