Some techniques, e.g. random forest, give variable importance indicators for free. If you can test it out, give it a go - don't have to use the random forest as the final model.
You can use correlation or the coefficients of a linear model iff the features on the same scale. Another method is to train a model leaving out each feature once, then you see how much accuracy drops.