Word sense disambiguation is an important intermediate stage for many natural language processing applications, especially transformation from Cyrillic into Mongolian script. A word sense could be disambiguated by other words in the context as nouns, verbs used with the word. In this research, we have analyzed the result of an experiment on a word disambiguation system for Mongolian language based on statistical model, to which one sense per collocation algorithm is applied, and suggested a model established of the weight of sense rate and the weight of distance to the adjacent words to improve the accuracy. We chose one of 1.7 thousand words which have more than one sense that were used in the experiment, and performed an experiment on 41 thousand words. We researched one of 6.3 thousand words which have a complex stem that can be considered to have another stem plus a suffix structure. Since it is the first work in this field for Mongolian language no previous work results were available for comparison.