Disclosed herein an incident prediction system and a method for predicting catastrophic incidents in a service system. The system receives one or more tickets for one or more services along with information of the one or more tickets. Further, the system identifies a set of tickets for each of a predefined event window and a predefined non-event window from the one or more tickets and identifies a set of words for each of the set of tickets using a prediction model. Furthermore, the system identifies cluster data for each set of tickets from pre-defined clusters using a ticket clustering model and identifies presence of one or more sequence rules in cluster data. Finally, the system generates a risk score for each of the one or more services and root-causes for the set of tickets based on the one or more sequence rules, one or more parameters and creation time.