Abstract: This study present a hybrid forecasting method with time series and intelligent error modification. It takes the historical income data of 19 months of a enterprise as the primary data, respectively using time series and grey forecasting method to train the data and to compare their results. It reveals that time series method is more accurate. However it can not meet the actual requirements. Through analysis, major income was selected from hundreds of items by using principal factor analysis method. Then, time series method was used for training major income respectively, next the large random items of income were operated with intelligent processing technology such as linear regression, neural networks and support vector machine for error modification. The result shows that the method with support vector machines is the best one.