Based on the weather phenomenon data from six national weather stations in northern Bayingol Prefecture of Xinjiang, China, the climatic characteristics of rain, snow, sleet, and rain to snow from October to April in the last 58 years (1961—2018) are analyzed. The results show that the major precipitation types in northern Bayingol Prefecture are rain in October and April, snow in December and January, and sleet and rain to snow mainly occur in November and March. The discrimination criterion and index of precipitation types are quantified using 10 physical variables closely related to the precipitation types transition discovered using sounding data from the Korla station from October 2003 to April 2018. The results show that: (1) Surface minimum temperature, near-surface air temperature, temperature at 850 hPa, geopotential thickness between 500 hPa and 850 hPa, geopotential thickness between 700 hPa and 850 hPa, and 0 ℃ level height can completely distinguish the four precipitation types, and the temperature difference between 500 hPa and 850 hPa, temperature difference between 700 hPa and 850 hPa can distinguish rain, snow, and sleet better. (2) A phase state scoring method for precipitation forecasts was developed, and after a thorough analysis, the combined index accuracy was 92.06% and 94.36% for Korla-Yuli-Luntai Plain and Yanqi Basin, respectively, and the forecast score was 93.58%. (3) The characteristic layer temperature and temperature difference forecast rain and snow with more accuracy than sleet, the geopotential height and thickness forecast snow with greater accuracy than rain and sleet, and the geopotential thickness forecast rain to snow with greater accuracy than the characteristic layer temperature. These comprehensive precipitation type indices have a high reference value for distinguishing precipitation types in northern Bayingol Prefecture and can provide a scientific foundation for improving rain-snow phase transition forecasting accuracy.