Monitoring condition and quality indicators within river water systems has emerged as a pressing priority due to the decline in water quality. This decline is primarily a result of improper disposal of household waste and the discharge of partially treated or untreated sewage and industrial effluents into the neighboring water bodies connected to the river systems. Conventional techniques for assessing water quality are costly and intricate and demand significant labor. Instead of relying on conventional field sampling methods, the utilization of cost-effective satellite imagery holds significant potential for the foreseeable future. This current study focuses on employing LANDSAT-8 OLI imagery to assess the Brahmani River's water quality parameters over 5 years, from 2017 to 2021. The selected water quality parameters encompass Biochemical Oxygen Demand (BOD), Dissolved Oxygen (DO), pH levels, Total Coliform (TC), and Fecal Coliform (FC). To determine the reflective values of all bands relevant to the aforementioned water quality parameters at their respective sampling sites, the Sentinel Application Platform (SNAP) tool was employed. Valuable insights were gained by establishing linear correlations between the water quality parameters and the reflective values of the bands and band ratios. Notably, the Pearson Correlation Coefficients revealed strong associations, with values of 0.892 for pH and B3/B7, 0.746 for DO and B1/B2, 0.814 for BOD and B7/B6, and 0.875 for FC and B6/B3. However, no robust correlation was observed between TC and any of the band ratios. The coefficients of determination for pH, DO, BOD, FC, and the corresponding band ratios (B3/B7, B1/B2, B7/B6, B6/B3) were calculated to be 0.796, 0.765, 0.772, and 0.766, respectively. Utilizing the outcomes of the linear regression analysis for pH, DO, BOD, and FC, predictions were made for the water quality parameters in the years 2020 and 2021. Impressively, a strong alignment was evident between the projected and observed values. This led to the conclusion that the established equations exhibited a noteworthy capacity to accurately predict the water quality parameters for the Brahmani River.