Eating behaviors are influenced by many factors including appetitive traits. Few studies have utilized latent profile analysis (LPA) to examine food approach and food avoidance appetitive traits. This study utilized LPA to define cluster profile groups based on appetitive traits in undergraduate and graduate/professional students at a large University in the southwest United States. Students completed a cross-sectional online survey in fall 2020 assessing demographic information, appetitive traits via the Adult Eating Behavior Questionnaire (AEBQ), and anxiety via the Generalized Anxiety Disorder Scale (GAD-7; higher scores indicate more severe anxiety symptoms). Appetitive traits were combined into eight scales (four food approach and four food avoidance traits). Latent profile analyses were conducted to identify homogenous subgroups of participants based on AEBQ scale scores. The final sample included 1243 students (mean age = 26.5 years, 73% female, 59% White, 57% undergraduates). LPA revealed four cluster profile groups: Cluster 1 (moderate eaters: lower than mean scores for food approach and avoidance traits), Cluster 2 (food seekers and avoiders: higher than mean scores for food approach and avoidance traits), Cluster 3 (food seekers: higher than mean scores for food approach traits), and Cluster 4 (food avoiders: higher than mean scores for food avoidance traits). Distribution of age, gender, race/ethnicity, and student status differed significantly between clusters. GAD-7 score was highest in Cluster 2 (food seekers and avoiders) and lowest in Cluster 1 (moderate eaters). Among the four LPA-defined cluster profile groups, students who endorsed both food approach and avoidance traits reported more severe anxiety symptoms compared to moderate eaters, food seekers, and food avoiders. It is useful to consider clusters of appetitive traits instead of individual appetitive traits when examining associations with physical and mental health.