An electronic microtongue using an electrochemical microcell was designed to monitor wastewater quality. The planar electrochemical microcells were micromachined in a microcrystalline Boron Doped Diamond (BDD) thin layer using a femtosecond laser. The electrochemical measurements with these BDD microcells were conducted using Differential Pulse Anodic Stripping Voltammetry (DPASV) for the major detection of heavy metal ions. Global signal obtained for raw wastewater (influent of Waste water Treatment Plant (WWTP)) and for water from Arve river were found much higher than those of treated wastewater (effluent of WWTP) and of treated wastewater from hospital. The DPASV signals have been processed by Principal Component Analysis (PCA) and K-Nearest Neighbours (K-NN). According to PCA results, waters were identified and discriminated with 99.75 % of the total variance of the dataset. Using K-NN with cross-validation approach, a good performance of the developed model was achieved for K=1 and 100 % of the samples were able to be classified in their original groups.