Using machine learning and other cognitive approaches to understand how to take past/existing behavior and predict future outcomes or help humans make decisions about future outcomes using insight learned from past behavior/interactions/data is a core part to which pattern(s) of AI?

Predictive Analytics & Decision Support (PA&DS) applies statistical / machine-learning models to historical data in order to estimate future states or recommend actions that improve decision-making. The description—“take past/existing behavior and predict future outcomes or help humans make decisions”—matches the exact definition of PA&DS given in the CPMAI v7 AI-Pattern catalogue.

A. Goal-Driven Systems reason over goals/rules to plan next actions; they do not necessarily use past data for prediction.
B. Adds “Patterns & Anomalies,” which centers on anomaly detection rather than forecasting; the question mentions only prediction/decision support.
C. Recognition Pattern classifies or labels current inputs, not future outcomes.

1. Cognilytica. “Cognitive Project Management for AI (CPMAI) v7 Handbook,” Sect. 3.2.4, p. 34: “Predictive Analytics & Decision Support uses prior behaviour to predict future events and inform decisions.”

2. Russell & Norvig. Artificial Intelligence: A Modern Approach, 4th ed., Ch. 2, p. 35 (decision support definition).

3. MIT OCW 6.864, Lecture 4 notes, p. 5 (predictive modelling concept).