In the field of forecasting, there are always more than one method to deal with a problem, and more than one institute will supply their own research on the same problem. It’s hard to say which method or information source is better, so the research how to make full use of all the information that we have is valuable. In this paper, we proposed a new fusion method to make full use of all kinds of forecast information to improve the performance of forecasting and made an application to oil price forecast fusion by it. This approach presented a stable and great performance. What’s more, it doesn’t require training data, little limit of the source data, no complex computation, and it also provides a solution to combination puzzle.