MORL-Baselines implements a collection of Multi-Objective Reinforcement Learning algorithms in PyTorch. The library follows the MO-Gymnasium API standard, where environments return a numpy array as reward instead of scalar values. It provides reliable implementations for training agents in multi-objective MDPs where rewards are vectors representing multiple competing objectives. The repository includes various MORL algorithms for researchers and practitioners working on decision-making problems with conflicting goals.