Marshal is a digital personal assistant for model-based systems. As organizations apply systems in new situations and expect new behavior, the system model may no longer characterize the environment — the model is vulnerable to drift. Marshal reins in drifting models to ensure they best match the current environment. Marshal combines user events, answers to clarifying questions, and experimentation to actively correct its knowledge of the system model. With up-to-date models, Marshal suggests corrections, maintains provenance, and predicts future model drift. Marshal reduces the cost and latency of ongoing model maintenance. SIFT has applied Marshal to maintaining NASA planning and procedure models for crew planning and Extra-Vehicular Activity (EVA).