Climatic changes affect not only the average precipitation but also the statistical structure of precipitation distribution, such as the frequency of extreme events, the skewness and kurtosis of the series. Therefore, in this research, for a deeper understanding of the impact of climate change on precipitation, the change in the probability functions of the precipitation data series was investigated. The length of the statistical period studied was t from 1951 to 2025, which includes 87 stations with 40 to 75 years of data. First, the change points were detected using the Pettitt method, then the best-fitting probability distributions for the series before and after each change point were determined and analyzed. The results indicated that, with few exceptions, the precipitation probability distributions before and after the change points differed at nearly all stations and in all months with significant change points. This suggests that, in addition to changes in the mean, other statistical characteristics of the precipitation series also changed, reflecting substantial shifts in precipitation patterns. After the change points, most stations exhibited a decrease in the probability of heavy precipitation and an increase in the probability of low precipitation, indicating a rise in the frequency of weak or short-term precipitation events. In other words, the probability density in low-precipitation intervals increased significantly. This pattern suggests that the precipitation regime in most stations with significant change points has shifted toward drier conditions, with the dominant precipitation systems losing capacity to produce heavy rainfall.