Abstract In order to improve predictive accuracy ofthe multi-point grey model, background values are selected by automatic optimization weights such that the residual sum of squares of the actual and fitted values is minimal. Caseresults show that, compared with traditional multi-point grey model, prediction accuracy is greatly improved with the background values optimized grey model.