DoubleML provides an implementation of the double/debiased machine learning framework for causal inference problems. It is built on top of scikit-learn and implements the methodology from Chernozhukov et al. (2018), allowing users to estimate causal effects using arbitrary ML models as base learners. The package targets econometric and statistical applications requiring valid inference after machine learning predictions.