In this paper, a deep review is conducted on Artificial Neural Network. ANN is used for real-world problems which are related to the hydrological field. Computational Intelligence methods such as Artificial Neural Network are very necessary because conventional methods are very complex and vexatious. Artificial Intelligence operation is based on the transformation of unknown relationship into the known sensible relationship, and hence this transformation helps in modelling real-world problems. Various applications of AI operation are carried out at present time, such as Rainfall-Runoff modelling, Groundwater modelling, water quality modelling, modelling stream flow etc. In recent years, Artificial Neural Network has shown exceptional performance as regression tools, especially when it is used for pattern recognition and function estimation. This paper mainly focuses on various ANN models for solving real and complex hydrological problems with great accuracy, and these are proposed as efficient tools for prediction in hydrology.