As an atmospheric parameter, air temperature plays an important role in providing energy to plants during their phonological stages. Soil surface temperature affects chemical reactions in plants, which is an important factor in nutrient uptake. Soil surface temperature is therefore an essential parameter in the quality and quantity of agricultural products. Advances in artificial intelligence and their applications across all branches of science provide us with tools to more accurately calculate and predict climatological parameters. In this paper, we use artificial neural networks to predict future soil temperature from five measured parameters, namely "minimum soil temperature", "humidity", "minimum and maximum soil temperature". air” and “the total number of hours of sunshine per day”. The data is collected at the Isfahan Synoptic Center and includes statistics from 1968 to 2005. Of these, 80 percent is used as the training set and the rest is used as validation data. Data analysis was performed using standard statistical methods using MATLAB. The learning methods used are linear regression and artificial neural networks. The results show that a neural network performs slightly better than linear regression, but the magnitude of the improvement does not justify the use of more complex models. Key words: forecasts, air temperature, soil temperature, linear regression, artificial neural network, synaptic data.1. IntroductionThe quality and quantity of food production is considered one of the most important problems of our world. Since a region's agricultural capacity for food production depends on climate, the study of factors affecting climate is of paramount importance. One of the main threats to food production is frost. For this reason, protect the place......middle of paper......s, to the east. Isfahan, with an area of ​​15,825 square kilometers and an altitude of 1,550.4 meters above sea level, is located on the central Iranian plateau (VP of Strategic Planning and Supervision of the Statistical Center of Iran, 1385: 300). In order to check the temperature status of the city, the available recording period (2005-1951) of the Isfahan synoptic station was used. The city's average annual temperature is 16.2° Celsius. The average minimum and maximum temperature are 9.1 and 23.4 degrees Celsius, respectively, corresponding to the months of January and July. The temperature difference between the hottest month and the coldest month is 25.5 degrees Celsius. The average monthly relative humidity is 40 percent, according to the station's long-term statistics. The overall annual precipitation is 122.8 mm and the average annual atmospheric pressure is 841.3 millibars..