Established ML algorithms are preferred models to study the dynamics of biofilm development, such as NB, RT, and RF . These algorithms have high prediction accuracy and provide an in-depth understanding of the impact of physical factors on biofilm development in engineered water systems. For instance, a Bagging naïve Bayesian tree (B-NBT) model proposes optimal flow velocities for different types of pipes to mitigate biofilm development . Predicted biofilm development probabilities show that, to control biofilm accumulation, water utilities need to avoid cement pipes, implement medium-or high-flow velocities in metal pipes, and sustain water ages above 0.035 in plastic pipes.