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This study aims to classify latent classes based on changes in the depression levels of patients with chronic illness and to confirm the influencing factors. The subjects of this study were 2,202 adults who had consistently shown chronic illness from the first to sixth surveys in the data of Korean Longitudinal Study of Ageing. The growth mixture model was applied to develop latent classes as per changes in their depression levels. Based on the change patterns of chronic illness patient depression level, our studies supported a four-class model defined as stable low, decreasing, increased then decreasing, and increasing class. Our results revealed that sex, age, income, difficulties on ADL, chronic illness severity, and duration were significant determinants of latent classes. In particular among these factors, difficulties on ADL, chronic illness severity were common factors that are likely to make those patients belong to the remaining three potential classes in reference to the stable low group. Healthcare practitioners should anticipate how the trajectories of depression in patients with chronic illness will demonstrate different changes in future and develop intervention strategies for each latent class.