Inspired by the sustained popularity of the Gradient Boosting Regression Tree (“GBTR”) algorithm, we go back to square one in an attempt to complete a from-scratch implementation in Python. This paper documents a journey from the basics of the regression tree algorithm through gradient boosting and concludes with an example implementation and a controlled simulation study. The outcome is a reliable open-source code base, which in the future will serve as an excellent platform for additional improvements and optimization.