Agricultural systems are incredibly complex and important systems, responsible for providing the world with food. The output of agricultural systems are made up of a large number of variables which contribute to the final yield of the system. These variables such as air temperature, rainfall, air pressure, and wind speed all have significant influences on soil temperature which is vital for understanding when to harvest produce and when to plant produce. We aim to use machine learning and statistical models to predict and forecast soil temperature based on weather data.