Water quality indices (WQIs) have become an essential tool for communicating the quality of water resources for drinking and different purposes globally. This method has been reported to be used in America, China, India, Iran, Brazil, Italy, Malaysia, Turkey and Spain. This review aims to identify the methodological approaches and gaps in the application of water quality indices in Nigeria water bodies. The review will encourage researchers to upscale studies using water quality indices methodologies to close knowledge gaps in this area. A total of 41 peer-reviewed articles published between 2014 and 2024 were examined, analyzing trends in water quality assessments, selection of indicators and weighting, statistical and chemometric tools, integration with machine learning and GIS, bioindicators and alternative indices. The results reveal that microbial and emerging contaminants are often excluded from WQI calculations, leading to under estimation of health risks. Furthermore, many WQI models are adapted from international frameworks without sufficient local calibration such as integrating multivariate statistics, macroinvertebrate indices, fuzzy logic, multilayer perceptron artificial neural networks and multiple linear regression models to validate water quality results. In addition, weight assignment and parameter selection remain subjective, and uncertainty quantification reduces the integrity of results. ‘Base on the output of this review, it is recommended that Researchers in water quality should always include physical and bacteriological parameters to reduce health risks associated with bacteriological contaminants. Develop a unified water quality model for Surface water, groundwater, and rainwater to enable standard measurement across the country. This will give the basis for comparing water quality results across geographical locations. Lastly, more work is required to standardize parameter selection and weight assignment in computing water quality indices.