Climate change is a statistically significant change in the average time series of long-term data (decades and more) related to climate in the region. Significance of the climate change, looking at its impact on the process and cycle of ecosystems and climate patterns on a regional and global scale, the occurrence of phenomena such as severe floods, droughts, global warming, severe heat and colds, changes in atmospheric synoptic and dynamic patterns and so on are evident. These impacts have implications in many areas of life including economics, agriculture, tourism, water resources, urban life, health and many more. For this reason, a regional study of this subject seems necessary and is one of the most important global issues of concern to politicians, economists, researchers, and other relevant individuals and institutions. In this study, using 30-year meteorological data of five stations in Guilan province and calculation of potential evapotranspiration, climate change in the region for a number of parameters, as well as the precipitation climate indices investigated. Trend analysis results with methods statistical and graphical Mann-Kendall tests, simple linear regression and climate indices were in agreement with each other. Significant levels of 0.1, 1, 5 and 10 percent used in the analysis of the results. The results showed that there is climate change in the region due to wind speed and potential evapotranspiration whit significant increasing trend and due to variable relative humidity whit significant decreasing trend. For example, the city of Rasht had increasing trend of 0.27 meters per second in the decade for the wind speed, 33 mm per decade for total potential evapotranspiration per year, as well as, a decreasing trend of -0.45 mm per decade for daily average humidity, over the 30-year period studied. Precipitation variables and indices do not have sufficient significant levels for climate change. The overall results indicate that these climate changes are the most dependent in summer and the least dependent in autumn.