The future state of the atmosphere is determined by weather forecasts. The change in weather conditions due to global warming and climate changes increases the importance of forecasting accuracy. Air temperature plays an important role in the determination of many activities such as agriculture, industry and so on. A certain temperature value is needed for the growth and development of plants. Plants are adversely affected when the temperature is high and varies. For these reasons, air temperature estimation has become important in countries with Mediterranean climate and in areas where greenhouse activities are intense. In recent years, the number of future weather forecasts and research has increased considerably. In this study, the average monthly air pressure was estimated by using artificial neural network method by using real monthly average vapor pressure, monthly average relative humidity, related month and year data of Antalya between 2000-2016.The artificial neural network model performance has been compared with statistical techniques. As a result, it was observed that the estimated values in the artificial neural network model have been consistent with the actual average air temperature values.