Microbial drinking after quality is essential to public health and the economic development of society . The microbial community in drinking water is highly diverse and ever-changing spatiotemporally, especially in engineered water systems . Therefore, monitoring and ensuring microbial drinking water quality is complex, time-consuming, and often ineffective with conventional assays. Microbes in drinking water encompass general heterotrophic bacteria, fecal contaminants, microbial indicators, protozoans (such as amoebae, ciliates, and slime molds), and OPs . Because of the complex nature of microbial drinking water quality, ML models are the preferred approaches for analyzing and ensuring microbial drinking water quality . This section summarizes the applications of ML in monitoring, predicting, and ensuring microbial drinking water quality (Table ).