Aiming at the problem that fuzzy clustering needs to know the best cluster numbers, a new validity index named new validity index for fuzzy clustering based on belong proportion is proposed in the reference of existing cluster validity indexes. Firstly, it proposes a basic validity index after full consideration of the given dataset's partition matrix and geometrical structure by redefining the separation distance between different clusters. Secondly, it defines the concept of belong proportion to enlarge the calculation value. Finally, it introduces cluster number to restrain the index because belong proportion may cause excessive influence. The new validity index is proved to be more reliable and have a higher accuracy compared to the classical indexes like XB index because it still makes right decision even when the given dataset is overlapping, so the new index has some value to popularize.