Decision Trees for Regression?

Personally, I have had really good experience with using decision trees for regression tasks, especially with bagged ones, in particular random forests. After all, they are quite well to interpret. Explainability is also good and with structured data (which is not super huge) and a limited amount of features, in which you can model your domain knowledge, they are a really good alternative or benchmark to Gaussian Processes in my opinion.

Also boosted trees work also often well.

I believe these threads might be relevant:

Happy learning!

Best regards