The analysis of gases dissolved in oil is the main technique used to predict possible failures in power transformers. Currently, there are some assessment algorithms for the predictive analysis, but all of them have in common the fact that they are based on the classical gas formation theory. This work aims to analyze the use of decision trees (DTs) for the analysis of gases dissolved in mineral oil, also establishing a relationship associated with decision-making during the formation of trees and the formation of gases. In this way, some important aspects involving the insulating mineral oil can be better understood and quantified. For this purpose, two data sets containing 162 and 201 samples are used in the study. The results provided by the tree are arranged in a Cartesian plane and the gases are analyzed based on the ratios used by Doernenburg. DT is discussed in detail to validate the algorithm performance based on the classical gas formation theory.