The main indicator used to assess the condition of solid insulation in power equipment currently is the degree of polymerization (DP). This work presents a systematic study where machine learning techniques are used to estimate DP from 2-fal and other indicators. The results are promising, indicating that 2-fal, CO$_2$/CO, the Chendong formula, and equipment power can be used together to better predict the current value of its service life.