In recent years the Box-Jenkins method has become a popular technique for forecasting future behavior of a time series. Once the forecast model is known the method is very easy to employ and adequate computer packages are available for most purposes. Ur .fortunately the problem of determining the appropriate forecast model has, for models of any complexity, been one of the major stumbling blocks to the user of this method .In this paper a satisfactory solution to that problem is obtained and it is demonstrated by numerous examples how this greatly enlarges the class of data sets which can be adequately modeled by autoregressive-moving average models . This new approach is sufficiently unequivocal that most users will find it ea~-y to implement.

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