This study is aimed at developing a neuro-fuzzy model with the Matlab Graphical User Interface (GUI) for calculating the biocoagulant quantity needed for turbid water clarification. A neuro-fuzzy network (NFN) was developed for three different levels (low, medium and high) of turbid water. Experimental turbid water bioclarification data were used, in the Matlab environment through a sub-clustering neuro-fuzzy function, for modelling NFN. The network consisted of four inputs (untreated water turbidity, untreated water pH, settling time as well as treated water turbidity) and Mango Kernel Coagulant (MKC) dosage as the output variable. The best NFN architectures that produced minimum percentage error were considered for biocoagulant dosage calculator GUI development and implementation. The experimental data and results obtained from the NFN-GUI calculator were compared; and the prediction of the dosage has Root Mean Square Error (RMSE) as well as correlation coefficient ranges of 0.01–0.10 and 0.93–0.99 respectively. The high correlation coefficient found in this study indicates that the NFN-GUI calculator is a perfect match with the traditional jar-test calculator. Therefore, the Matlab-based calculator template is able to predict the biocoagulant quantity needed in a community water bioclarification treatment unit.