Probability estimation is a research area within statistics and machine learning that focuses on estimating the likelihood of an event or outcome occurring based on available data. It involves developing models and algorithms that can accurately predict the probability of different events or outcomes, such as the likelihood of a customer making a purchase or the probability of a patient having a certain disease. Probability estimation is used in a wide range of applications, including risk assessment, decision-making, and predictive analytics. Researchers in this field explore various statistical methods, machine learning techniques, and data analysis approaches to improve the accuracy and reliability of probability estimates. The goal is to provide valuable insights and predictions to help individuals and organizations make informed decisions and take appropriate actions.