Rainfall prediction is a significant and demanding task in today’s world. Due to the nonlinearity and complication, rainfall and climate require advanced computer modeling and simulation to predict accurately. This paper comes up with a comprehensive survey and a fair comparison of several types of neural network architectures for rainfall prediction and mentions the challenges of using traditional and advanced methods in doing this task. Finally, the paper discusses the utility of deep learning methods for rainfall forecasting.