Predictive quality refers to the ability of a model or algorithm to accurately predict future outcomes based on historical data. It is typically evaluated using metrics such as accuracy, precision, recall, and F1 score. Factors that can affect predictive quality include the quality and quantity of training data, the complexity of the model, and the choice of algorithm or technique used.