Evaluation of pharmacokinetics and pharmacodynamic properties through in silico approaches has proven to characterize and determine the drug-likeness properties of lead compounds in drug discovery programs. It minimizes the threat of expensive, lengthy, and unsuccessful drug trials. To improve the accuracy and reduce costs in veterinary drug development, it’s widely acknowledged that computer-based predictions of drug-likeness and toxicity should be considered early in the drug discovery process, before conducting in vitro and in vivo tests. Failures in late-stage drug development are often due to poor pharmacokinetics and pharmacodynamics. It is important to validate vetinformatics predictions through experimental studies to fully assess the safety of lead compounds before clinical studies on livestock. This chapter focuses on analyzing drug-likeness and toxicity prediction for therapeutic roles in veterinary applications. The development of predictive models like quantitative structure–activity relationship (QSAR) facilitates efficient optimization of absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties in lead compounds. Early toxicological predictions can assess the reliability of potential compounds and prevent adverse effects on livestock systems.