A new article proposes a simple and effective hybrid generative model that can predict unseen domain boundaries in synthesized materials with limited observations, without the need for expensive calculations or simulations. The study highlights the potential of simple and interpretable machine learning models in describing and understanding the nature and origin of disorder in complex materials, leading to improved functional materials design.