Water plays a pivotal role in everyone’s life. Water is necessary for all life to exist and grow. However, people frequently take its availability for granted, despite the fact that water is essential to existence. There are several problems regarding water that is concerning and needs to be addressed. In a residential area, the primary issues faced include water shortage, wastage of water, supply of poor quality water, ineffective water monitoring system, etc. All of this leads to poor water management and thus the residents suffer. Thus it’s critical to develop an effective water monitoring and management system for proper water management. In this paper, the problem is addressed and solution is provided through dynamic water management system using LabVIEW and machine learning. the system offers predictive capabilities that allow users to estimate the total duration till the current volume of water is completely exhausted (available hours of water supply) and total duration till the tank refills completely (tank refill duration) based on the current water level in a tank. The main aim is to build a system that not only minimizes wastage of water but also enhances the overall effectiveness of water management. The data set was generated using LabVIEW software which simulated a water management system similar to the real world environment. Linear Regression machine learning algorithm was selected and applied to the data set for prediction of the required variables and the result obtained has 94.56% and 99.24% accuracy for Available Hours of Water Supply and Tank Refill Duration respectively. This system not only minimizes wastage of water but also enhances the overall effectiveness of water management.