Chemoinformatics utilizes computational methods to examine chemical data and forecast the properties of compounds. Machine learning enhances this by discovering patterns and making data-driven predictions. Applications include virtual screening, toxicity prediction, and de novo drug design. These tools accelerate decision-making and reduce experimental burden. Integration with AI is transforming drug discovery pipelines.