Monitoring the status of ongoing sales opportunities in IT service engagements is important for sales teams to improve the win rate of deals. Existing approaches aim at predicting the final outcome, i.e., The eventual chance of winning or losing a deal, given a snapshot of the deal data. While this type of prediction indirectly advises on the deal status, it offers limited guidance and insights. During the engagement progress, there occur numerous milestones and key events whose occurrence and status is important in achieving the desired outcome of the deal. These interim milestones and events may happen in different time intervals during the lifecycle of a deal, depending on the deal size and other parameters. In this paper, we describe a novel Bernoulli-Dirichlet predictive model for predicting the occurrence of key events and milestones within a service engagement process to assist in monitoring the progress of ongoing deals. This model enables predicting the timeline and status of the next event(s), given the current history of milestones activity in the engagement lifecycle. Through such a step-by-step guidance, sales teams may have a higher chance of success by knowing of upcoming events, and preparing to counter undesired events. We show the empirical evidences of significance and impact of such an approach in a real-world service provider environment.