Most of the clustering objects have the characteristic of multiple heterogeneous uncertainty in real life, which is presented via the heterogeneity of the clustering indicator system of objects and multi-uncertainty of the objects information.However, the present uncertainty multiple attribute clustering decision methods have limitations to research the clustering of these kinds of objects.Therefore, firstly the concept of generalized interval grey number is proposed according to the characteristics of multi-uncertainty information.It is proved that multi-uncertainty information can be all represented with generalized interval grey number in some specific conditions.Then, the rule of maximum entropy is introduced, the generalized interval grey entropy-weight allocation model based on multiple heterogeneous uncertainty cases study is built.The entropy-weight of multiple level is calculated through studying the cases about the objects, and then the weight of every indexes is got.Furthermore, the white function of generalized interval grey is used to analyze the clustering for the new cases of objects.Finally, the case study verifies the rationality and feasibility of the proposed clustering model.