One of the most valuable resources is water. About 70% of the earth's surface is covered by water, which is one of the most critical resources for maintaining life. Water must be suitable before usage because it is used for a variety of uses. Rapid industrialization and urbanisation have caused an alarming rate of water quality degradation, which has resulted in terrible diseases. Water sources need to be routinely checked to see if they are still safe to use. Since water quality has traditionally been determined by costly and time-consuming statistical and laboratory investigations, real-time monitoring systems are now required. This research investigates a number of supervised machine learning techniques to calculate the water quality index using this as its inspiration. With the use of Machine Learning Model, there will be no limitation of the complexity increasing the number of variables.