This review centers on incorporating machine learning (ML) algorithms to improve strategies for trading options. The study investigates different ways ML can be integrated into options trading, such as handling market data, forecasting trends, and improving trading decisions with greater precision and speed. The process includes collecting information from sources such as Yahoo Finance and then carrying out pre-processing, selecting features, and building models like logistic regression and multinomial models. Important components of the study involve analyzing various strategies in options trading, utilizing sophisticated machine learning techniques such as deep learning and reinforcement learning, and developing an algorithmic trading bot. The performance analysis of models assesses how machine learning enhances trading strategies. In addition, the article discusses issues regarding extracting features, interpreting models, and the ethical impacts of automated trading systems. The results show that ML greatly improves the accuracy of forecasts and decision-making in options trading. The suggested system showcases the merging of ML models into algorithmic trading bots, streamlining and enhancing trading operations. The article ends by talking about possible areas for future investigation and enhancements to further perfect ML applications in financial trading.