Breast cancer is one of the biggest scourge affecting women today. Different methods are often used in treating breast cancer; however, the post treatment phase can be very difficult for patients with over 90% of treated breast cancer patients suffering treatment-related side effects months after treatments. This paper studied and identified the patterns in which these occur, the possible reasons why some type of side effects occurs in some patients and not in others. This will help oncologists to predict the post treatment phase of a patient given the treatment method to be used and other inherent factors the system will learn from the data analyzed. Neural network was used to develop a system capable of learning the underlying patterns in the data collected from different cancer care centers. The system is cloud-based; to enable easy access to data from different locations and subsequent pattern analysis on them. Our system is able to detect certain factors in some patients showing why they react to treatment processes the way they do. This system will help oncologists decide the best course of treatment to administer to patient and manage patient recovery process. The methodology adopted is the object oriented Analysis and Design methodology. And the system was implemented using PHP.