I have longitudinal data (repeated measures on each subject over 't' time periods) with a binary response variable & various continuous/categorical covariates. I wish to build a forecasting model that tells the outcome for the time ahead: t+1, t+2... etc, while simultaneously regressing on the predictors, until time t. 

I want my model to use the information from the covariates at present time t, to forecast the response for the time ahead.

I believe that my model will predict the outcome with a probability associated with it, something like a Markov model + regression, that gives the state transition probability, also taking into consideration the covariates that affect the state.

Any help on how to structure the problem and/or implement it in R/SAS will be helpful.