Causal reasoning is the cognitive or computational process focused on identifying and inferring cause-and-effect relationships between variables or events. This involves understanding how changes in one factor lead to changes in another, distinguishing true causal links from mere correlation. As a research field and methodological concept, it investigates the mechanisms by which agents infer, represent, and utilize cause-effect structures from data or experience. Key characteristics include the capacity for counterfactual thinking, intervention planning, and predicting outcomes under hypothetical scenarios. Its significance lies in enabling robust explanation, prediction, and effective intervention across diverse domains of inquiry and application, from scientific discovery to artificial intelligence.