With the complexity of decision environment, the coexistence of multiple types of heterogeneous decision information is more and more common. To this phenomenon, the paper proposes a new transformation method to unify heterogeneous information into a set of random values by segmenting the data range into several subintervals based on its distribution characteristics. This method can improve the consistency of distribution structure between the transformed values and initial information as much as possible. Through large-scale simulation analysis, the solution method and conclusion of the optimal sub-segment interval in the random transformation process of heterogeneous information under different circumstances are summarized, which can provide reference for the determination of the sub-segment sampling interval in practical application. Further, the integrated aggregation method is fused with the random transformation process. Through the statistics of the superiority probability and ranking distribution probability between any two alternatives in the aggregation process, the possibility ranking result reflecting the relative advantages and disadvantages of alternatives is obtained. This type of ranking result achieves the flexible transformation of decision conclusion from "absolute form" to "relative form", which is more consistent with the diversity, uncertainty and fuzziness of the original decision information and is more interpretable and acceptable. Finally, the effectiveness of the proposed method is verified by comparison and analysis with existing examples. An application example is constructed on the background of comprehensive prediction of provincial development potential to illustrate the characteristics and application prospect of this method. This study further enriches the transformation approach of heterogeneous information and provides method support for complex decision-making problems with multiple types of information co-existing.