Although criminal justice researchers have devoted more effort to the testing of hypotheses concerning determinants of crime than they have to the prediction of future crime rates, forecasting models can be of service to criminal justice planners in a number of ways. The most straightforward approach to forecasting is to project the value of the crime rate into future periods by extrapolation from its values in prior periods. Techniques employed for this univariate approach include moving average, regression, and the Box-Jenkins technique. The primary disadvantage of this approach is that it has no behavioral content. A second approach, indicator tracking, addresses the underlying determinants of the crime rate, i.e., social or economic factors. Techniques employed with this approach include the multiple regression analysis, and Delphi techniques. System flow models and microsimulation draw upon the techniques of operations research to investigate the interactions of different elements in the criminal justice system. Perhaps the most promising approach to overcoming the limitations of the multiple regression models is the combination of several regression equations into a simultaneous system; each equation is used to specify the hypothesized behavior of one part of the system, e.g., the effect of police expenditures on arrest rates. Based upon review of the available approaches and techniques for the forecasting of crime, it is concluded that extrapolation by means of one of the univariate methods would be most appropriate for generating short-term forecasts at a reasonable cost. As the time horizon over which the forecast is to be made increases, so do the dangers of pure extrapolation. The use of a coherent theoretical model offers the possibility of long-term forecasts in approximate terms, and research activities should focus on its development. Such a model might include the definition and measurement of the risks and returns of crime for individuals according to specific characteristics; investigation of the risks and returns of alternative activities, such as legal employment; and investigation of social and environmental variables which might account for preferences with respect to legal and illegal activity. One table, 4 notes, and 27 references are included.