I know that the predictive horizon is the time window that runs from the observation of the data to the manifestation of the target variable.

But how can I deal with prediction if the time horizon varies in my dataset? I mean, how can I manage the prediction when the target variable is observed at a (known) variable time horizon with respect to the data?

Is it possible to train a simple logistic reression with the aim of having a 1 year prediction starting from a training dataset where the predictive horizon is varying (but known).

Thank you