Analyzing survey data for predictions
Can you give a bit more information on the size of the data you're training on (and if it's really 6 parameters you're basing the predictions off of)?  If it's really 6 questions with binary answers (1, 0 as you suggest), then there are 2^6 (i.e. 64) unique answer combinations, and to determine a probability for them you'll want a multiple entries per combination.  Standard error scales like 1/sqrt(n) so for 10% accuracy you'll need roughly 6,400 inputs which given your description, sounds like more data than you may have.  You may want to invest time into automating data collection.

If on the other hand, you have a reasonably large data set and are hoping for some alternative models, both boosted decision trees and random forest models sound like good candidates for this problem.