Dropout classifcation
There isn't a particular approach or model that is definitively the best. You might want to try multiple types of models. A good starting point would be to visualize your data. If there are many non-linear relationships between your data and the the outputs you are predicting then you might want to start with a tree based model. It will be much less work to make it perform well. If the relationship between your variables and the outcomes you are predicting are fairly linear then a logistic regression model is a good approach. 

If you have to have a silver bullet model to solve all your problems then I recommend trying xgboost. Use grid search and you will have a good model.

I actually worked on a similar project for my university. Aggressive feature engineering combined with logistic regression performed and xgboost were the two best models.