The concept of an artificial neural network (ANN) was to imitate the nervous system and human brain's activity. Comprehensive literature review revealed that ANNs are widely used in environmental engineering and are recognised in modelling of water quality index and waste-water treatment plant efficiency, as well as in predicting air quality index and noise pollution analysis. This study provides a review of various methodologies and applications in environmental engineering. Accordingly, articles were categorised based on methodology, approach employed, release year, authors, research goals, outcomes, discoveries, solutions, and modelling. A decent corporeal sympathetic ANN approach is summarised in this study. The most significant factors were identified and explained in detail, which will be considered while developing a more efficient neural network model. Furthermore, this research may aid civil and environmental engineers, as well as practitioners, in addressing engineering difficulties and comprehending the applicability of ANN against traditional mathematical approaches.