Objective: To explore the dynamic developmental trajectories of college students class belongingness during their college years and its longitudinal predictive effects on depressive symptoms, so as to provide targeted insights for precise campus psychological interventions. Methods: In October 2021 (T1), a total of 4 720 college students from a university in Shandong Province were selected by cluster sampling method and followed up for 3 years. Surveys were conducted annually (T2: October 2022, T3: October 2023, T4: October 2024). The Class Belongingness Scale and Patient Health Questionnaire-9 (PHQ-9) were used to assess students class belongingness and depressive symptoms. Latent growth mixture modeling was employed to identify trajectories of class belonging, and multinomial Logistic regression analysis was used to examine the predictive effects of these trajectory classes on depressive symptoms. Results: Mean scores of class belongingness across T1-T4 were (73.24±11.95, 74.76±12.25, 75.25±12.38, 77.64±11.63), and the scores of depressive symptoms were [1.00 (0, 5.00), 0 (0, 3.00), 0 (0, 2.00), 0 (0, 2.00)]. The developmental trajectories of class belongingness were categorized into three types: the high-starting ascending group ( 56.61 %), the low-starting descending group (11.91%), and the medium-starting stable group (31.48%). Multinomial Logistic regression analysis showed that, compared to the medium-starting stable group, the high-starting ascending group had a lower probability of developing mild depressive symptoms ( OR=0.27, 95%CI =0.15-0.47) and moderate or above depressive symptoms ( OR=0.29, 95% CI = 0.14-0.60) (both P <0.05). Conversely, the low-starting descending group had a higher probability of developing mild depressive symptoms ( OR=2.31, 95%CI =1.65-3.22) and moderate or above depressive symptoms ( OR=7.49, 95%CI = 3.82-14.69) (both P <0.05). Conclusion Declining trajectory of class belongingness is a risk factor for depressive symptoms, while sustained upward trend may mitigate such risks.