The quality of health care is affected due to crowding of Emergency Department(ED). To avoid the adverse effects of inconvenience and improve patient care, there is a need to explore ideas and innovative technology methods for predictions of admissions in ED. The analysis of data gathered from hospitals like the patient age, previous history, month of the year, day of the week and time of the day in which the patient was admitted in the ED for health care work as the key for predictions of future admissions using data mining techniques with the help of some machine learning algorithms. The usage of data mining techniques combined with the following three techniques logistic regression, decision trees, and (GBM) Gradient Boosted Machines give the final method for predictions of patient admission in ED. The advantages of using data mining.