Are Random Forests more powerful than generalized linear models?

One point to consider is are you interested in making predictions or understanding associations and carrying out inference (confidence intervals around effects). Although random forests provide a variable-importance summary, this technique is primarily aimed at prediction; there is no inference. Many researchers think they are interested in making predictions, but often there is a mismatch with their goals. With that said, you can make predictions with glm and gamlss. You also have the flexibility of regression.