Classification with feature not available at time of model creation
It seems the simplest way to go would be to build a line at each time step after 'time created'. With 'status_n-1', 'status_n'. That will allow to deal  with the notion of time in rows. You also might want to :


Deal with time relatively : instead of considering status at a given hour, you probably want to work with status since the creation of the task.
You will need to deal with task ponderation (longer tasks will get more rows) one way or another. You may add some ponderation in your model, based on 1/(expected length). 
Add some features : to me it is unclear what feature you use for prediction. As is, you seems to be trying to predict time of completion based on start time / expected length. You won't learn much except for which tasks takes more than expected / some daily effects. I think this can be achieved more efficiently / more clearly with simple statistics.