CancerCancer is sorted by widespread and atypical development of cells. This unrestricted maturation of cells donates to the tumor evolution. Each year, the incidence of breast cancerBreast cancer is escalating significantly making it a crucial disease amid women widespread creating it a remarkable common health issue in today’s mankind. Consequently, advancements in the forecasting and the detection of cancerCancer are crucial for promoting a wholesome well-being. Therefore, achieving a fine-grained accuracy in cancerCancer fidelity is requisite for strengthening treatment interventions and the overall viability of patients. Algorithms are employed to train a model on the dataset of patients. Feature selection is performed, and cancerCancer stage is predicted using selected features. Owing to breast cancerBreast cancer, numerous women pass away worldwide. The recommended model incorporates multiple Machine LearningMachine learning (ML) methods, including Logistic RegressionLogistic regression (LR), Random Forest ClassifierRandom forest classifier (RFRandom Forest (RF)), Artificial Neural NetworkArtificial neural network (ANN), XG Boost Algorithm.