Abstract: In the prediction of time series by using the periodic extrapolation of the variance analysis,and in double-test stepwise regression prediction,or in other analysis of related problems,there is a need to find the maximum from the F-statistics of several factors to be F-tested significant.However,this kind of test is in question and inappropriate,which might affect the exactness of climatic prediction.Note that F-test is to examine the quantile of the F-distribution and could be a variable value due to the examination standard limited by the two freedom degrees,thus the most significant factor and factor of maximum F-statistics may not be the same.In other words,it is not an appropriate way to use a maximum statistic value as a criterion to choose a significant factor,as the F-test is not exactly true to some extent.Therefore,a test of F-degree of confidence is proposed.It is a test for a distributional function of F-distribution.The F-degree of confidence of a factor is defined as the percentage of distribution function of F-distribution P_i=(1-α_i)×100%,which needs to calculate by using the F-statistic value and two freedom degrees.Given the significant level α,then the criterion of F-degree of confidence is P_α=(1-α)×100%.Theoretically,the criterion of F-degree of confidence is unique for the test so that it can be tested by choosing the maximum from several values of F-degree of confidence.The practice already proved that this test method could improve the ability for discriminating factor significance and predicting the climate.