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Introduction: To identify factors predictive of falls and enable appropriate management of fall risk it is necessary to understand the behaviour and health conditions of older adults living in nursing homes. Objective: This study had two main objectives. The first was to find significant predictors for falls in older adults living in nursing homes. The second main goal was to build a predictive model to find the best predictors for falls. Methods: Out of 56 nursing homes with the same legal statute, 25 agreed to participate. The sample was randomly selected and only the independent or slight/moderately dependent participants were included in the study (n = 325). Results: There was a mean of 1.47 ± 0.99 falls (range from 1 to 7) per resident in nursing homes. By using the t test and odds ratio analysis, ten factors related to falls were identified. Through the binary logistic regression, a model was tested identifying four robust predictors: static balance, resorting to emergency services, polypharmacy, and an independent self-care profile. Conclusions: The present study replicated the main results of contemporary research on the risk factors of falls. More importantly, it suggests that the self-care profile model should be taken into account in future studies and early interventions. It is crucial to implement preventive measures consistent with safer environments and to establish an individual plan for integrated activities according to older adults’ health needs.