A projection model is a special case of a mixed parameter model, which accounts for the variations among different stand growth curves by assigning a parameter as site-dependent or individual-dependent. Due to this property, projection models have been widely used in stand growth and yield modeling. This paper gives a general overview of applications of projection models in modeling growth of stands and single trees, mathematical properties of the models and relationships among their properties. The role of the initial value of the response variable (y1) and the effect of the random error term associated with y1 (e1) on model predictions were statistically investigated. The latest research about projection models mainly focus on the derivation of projection equations, estimation of parameters and analysis of prediction errors. We also discuss the generalized algebraic difference approach (GADA), parameter estimation methods and analysis method of prediction errors.