1. A computer implemented iterative method for predictive analytics in a semi-structured process comprising: updating, iteratively, at least one probability of a probabilistic process model for the semi-structured process based on a completed task, wherein updating the at least one probability of the probabilistic process model comprises: identifying a present state within the semi-structured process; deriving, from a process policy of the semi-structured process, a set of tasks, of a plurality of tasks associated with the probabilistic process model, that can be performed, at the identified present state, in conforming to the semi-structured process; establishing a todo list including the set of tasks that can be presently performed; defining a cost of each of a plurality of tasks of the todo list; prioritizing the plurality of tasks of the todo list according to the defined costs; and recommending a next task from the todo list according to the prioritization.
3. The method of claim 1 , further comprising updating the todo list by removing another task from the todo list.