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OBJECTIVES: Defining common patterns of recovery after an acute health stressor (resiliency groups) has both clinical and research implications. We sought to identify groups of patients with similar recovery patterns across 10 outcomes following hip fracture (stressor) and to determine the most important predictors of resiliency group membership. DESIGN: Secondary analysis of three prospective cohort studies. SETTING: Participants were recruited from various hospitals in the Baltimore Hip Studies network and followed for up to 1 year in their residence (home or facility). PARTICIPANTS: Community‐dwelling adults aged 65 years or older with recent surgical repair of a hip fracture (n = 541). MEASUREMENTS: Self‐reported physical function and activity measures using validated scales were collected at baseline (within 15‐22 d of fracture), 2, 6, and 12 months. Physical performance tests were administered at all follow‐up visits. Stressor characteristics, comorbidities, and psychosocial and environmental factors were collected at baseline via participant report and chart abstraction. Latent class profile analysis was used to identify resiliency groups based on recovery trajectories across 10 outcome measures and logistic regression models to identify factors associated with those groups. RESULTS: Latent profile analysis identified three resiliency groups that had similar patterns across the 10 outcome measures and were defined as "high resilience" (n = 163 [30.1%]), "medium resilience" (n = 242 [44.7%]), and "low resilience" (n = 136 [25.2%]). Recovery trajectories for the outcome measures are presented for each resiliency group. Comparing highest with the medium‐ and low‐resilience groups, self‐reported pre‐fracture function was by far the strongest predictor of high‐resilience group membership with area under the curve (AUC) of.84. Demographic factors, comorbidities, stressor characteristics, environmental factors, and psychosocial characteristics were less predictive, but several factors remained significant in a multivariable model (AUC =.88). CONCLUSION: These three resiliency groups following hip fracture may be useful for understanding mediators of physical resilience. They may provide a more detailed description of recovery patterns in multiple outcomes for use in clinical decision making. J Am Geriatr Soc 67:2519–2527, 2019 [ABSTRACT FROM AUTHOR]