Abstract: A computer-implemented method and system for determining a probability of incident occurrence resulting from one or more changes to one or more computer networked applications. A machine learning (ML) model is trained to identify probability of likelihood of one or more incidents from occurring to one or more computer applications attributable to one or more changes to the one or more computer applications. Information is received corresponding to at least one application change attribute, which is then analyzed by the trained ML model to identify one or more incident occurrence indicators applicable to the at least one application change attribute. A probability of one or more incidents occurring is then determined corresponding to the at least one application change attribute.