Song and Chissom authors presented the new concept of fuzzy time series for the first time. However, computational method of the fuzzy logical relationship groups in the fuzzy time series forecasting model is too complicated to apply. Thus, the forecasting accuracy is not high. Chen author changed the way to compute fuzzy relationship groups by simple numbers arithmetic operations in order to bring a better forecasting result. Hedge algebra (HA) is a new approach built by N.C.Ho and W. Wechlerx in the 1990s, 1992s as giving a dealing model of linguistic value of linguistic variable and it is completely different from fuzzy approach. As an application, this paper is a continuous process of the studies using hedge algebra in the field of fuzzy time series forecasting. This is a new field which is being studied by many scientists all over the world. Basing on data series of the historical enrollments of the University of Alabama from 1971 to 1992, the paper proposes a new forecasting method based on hedge algebra and compares to the results of Song, Chissom, Chen, Hwang and Huamg authors. Meanwhile, it can be shown that the mean squared error (MSE) by approaching hedge algebra is much less than the one in fuzzy time series forecasting model of the above authors.