A lab-scale study imitating microalgae-based wastewater treatment systems was conducted to evaluate the impact of microalgae Chlorella vulgaris on the removal of Escherichia coli from raw blackwater. The study consisted of three tests, each with a different dilution of blackwater: 10%, 30%, and 50% blackwater. A machine-learning method (Decision Trees induction) was employed to extract functional dependencies between the measured parameters: E. coli, and C. vulgaris concentrations, electric conductivity, pH, chemical oxygen demand, total nitrogen, ammonium-nitrogen, and orthophosphate. The results showed that electric conductivity was the most crucial parameter influencing E. coli inhibition. The removal of E. coli was achieved at an electric conductivity of ≤1569 μS/cm and C. vulgaris concentration >1 × 10⁷ cells/mL depending on the pH value. These results indicate a shift in C. vulgaris and E. coli interaction from mutualistic to competition at a threshold value of electric conductivity 1569 μS/cm at a light intensity of 5000 lux in 16/8 h light/dark intervals, constant temperature and regulated pH.