Predictive distribution is a probabilistic framework used to forecast future observations based on a model trained with existing data, capturing both the uncertainty of the model and the inherent randomness in the data. It is crucial in Bayesian statistics, where it integrates over all possible model parameters to make predictions, offering a comprehensive representation of uncertainty in predictions.