ToxiM is a machine-learning based binary classifier for the prediction of toxicity of molecules. Positive dataset comprises of known toxins with recorded medical consequences in low concentrations and negative dataset consists of metabolites found in the human body. Our models were developed on the basis of molecular properties which were converted into the input features, descriptor and fingerprints that are readable by the machine.