Abstract: In silico toxicology tools, steps to generate prediction models, and categories of prediction models. The purpose of this study is to provide a comprehensive overview of existing modeling methods and algorithms for toxicity prediction (element D above), with a particular (but not exclusive) emphasis on computational tools that can implement these methods (element E), and expert systems that deploy the prediction models (element F). Due to the nature of this expanding field, this study cannot provide an exhaustive overview of all the seven in silico components mentioned above. Prediction of Toxicity-associated properties of new chemicals is a big challenge. In admetSAR, probabilistic, regression as well as qualitative classification models were implemented for 'Human Ether-a-go-goRelated Gene Inhibition', 'AMES Toxicity', Carcinogenecity', 'Fish Toxicity', 'Tetrahymena Pyriformis Toxicity', 'Honey Bee Toxicity'.Among all the synthesized Pyrimidine derivatives (P1 to P5) , Pyrimidine derivatives P4 and P5 shows lesser toxicity.