Cancer is one of the medical conditions that causes many deaths in different parts of the world. Based on information obtained from GLOBOCAN, the International Agency for Research on Cancer (IARC) in 2022, there were at least 19.976.499 individuals diagnosed with cancer, and the disease caused death in 9.743.832 people. The detection of breast cancer malignancy relies on the prognosis process, requiring forecasting and automated detection to mitigate diagnostic errors. This facilitates swift and comprehensive analysis of medical data. The study employs the Neural Network, specifically the Artificial Neural Network model, implemented using python and the backpropagation algorithm. Utilizing data from the WDBC Database at the University of Wisconsin, the research achieves a 96,49% accuracy in breast cancer prediction, with an area under curve (AUC) value of 0,992, demonstrating the model's overall efficacy in accurate predictions.