Gam is best if you believe there are nonlinear relationships between the predictors and the outcome.  If your outcome is especially noisy, it's unlikely that you can detect most nonlinearities.  But with clean measures, it's worth a look.

Thanks Michael - that's really helpful.

Cheers

Joe

Furthermore, I suggest GLM for hypothesis testing, and GAM for predictive modelling.