Evaporation is a crucial factor in numerous hydrological and water resource systems initiatives. This research seeks empirical relations for computing monthly pan evaporation based on climatic temperature, relative humidity, and wind speed data. This study used 11 years of meteorological data (e.g., from January 2004 to December 2014). A parameter selection approach is utilized with multiple linear regression to determine the optimal model forms. Using the power and exponential functions, the correlations of evaporation with temperature and relative humidity different trendlines were fitted to identify the hidden pattern in meteorological data. The suggested evaporation estimating models with the optimal climatic parameters combinations were demonstrated to yield results that fit well with the observed data.