In the original paper, it is said that of the 117 metrics they used to identify technical debt (3 of the 10 categories, TBE):

The results were disappointing, to say the least. No single metric predicted reports of technical debt from engineers; our linear regression models predicted less than 1% of the variance in survey responses. The random forest models fared better, but they had high precision (>80%) and low recall (10%–25%).