The many problems of energy and nutrient flow and their relationship to the structure of communities and potential for harvest make primary productivity interesting. The correlation between the productivity and character of vegetation cover, and the potential for agriculture and the environmental aspects of cultural development, have created additional interest. This volume emphasizes the fact that assessment of primary productivity is a time-consuming and expensive procedure. In some cases, it is even logistically impossible to measure the current productivity rate directly. Under such circumstances, one is inclined to look for indirect ways to estimate the productive capacity of any given region. The most feasible approach to the task is the elaboration of models that predict productivity from environmental parameters that have been measured in a reasonably dense network over the world.We present and discuss three of the various attempts to build such predictive models. The first model predicts productivity from annual precipitation and temperature averages. This model was first presented at the 1971 Miami symposium and was publicized in summary form as the Miami Model (Lieth, 1972b(Lieth, , 1973. The development of this model is described in detail in this chapter.The second model predicts productivity from actual annual evapotranspiration. This model was developed for the C. W. Tho~thwaite Memorial Symposium at the 22nd International Geographical Congress in Montreal in 1972. Several maps were produced using various data pools. This set of models and maps was called the Montreal Models, and the second of these was named the

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