Background: Falls incidence rate and comprehensive data on factors that predict occasional and repeated falls from large population-based studies are scarce. This study aimed to determine the incidence of falls and identify predictors of occasional and recurrent falls within the social, medical, physical, nutritional, biochemical, cognitive dimensions among community-dwelling older Malaysians. Methods: Data from 1,763 Malaysian community-dwelling older adults aged ≥60 years were obtained from the LRGS-TUA longitudinal study. Participants were categorized into three groups according to the presence of a single fall (occasional fallers), ≥two falls (recurrent fallers), or absence of falls (non-fallers) at an 18-month follow-up. Results: Three hundred and nine (17.5%) participants reported fall occurrence at 18-month follow-up, of whom 85 (27.5%) had two or more falls. The incidence rate for occasional falls and recurrent falls was 8.47 and 3.21 per 100 person-years, respectively. Following multifactorial adjustments, being single (OR: 5.310: 95% CI: 1.963-14.361), having higher depression score (OR: 1.123; 95% CI: 1.045-1.207), lower hemoglobin level (OR: 0.873; 95% CI: 0.797-0.956), and taking a longer time to complete the chair stand test (OR: 0.936; 95% CI: 0.881-0.995) remained independent predictors of occasional falls. While, having higher depression score (OR: 1.116; 95% CI: 1.010-1.233), being a stroke survivor (OR: 5.639; 95% CI: 1.502-21.129), having higher percentage of body fat (OR: 1.038; 95% CI: 1.010-1.067), lower hemoglobin level (OR: 0.853; 95% CI: 0.741-0.982), and taking longer time to complete the chair stand test (OR: 0.907; 95% CI: 0.824-0.998) appeared as recurrent falls predictors.Conclusions: Having depression, lower muscle strength and hemoglobin levels predict both occasional and recurrent falls among Malaysian community-dwelling older adults. This finding has implications for future research planning, which should aim to identify effective strategies for preventing falls among older adults by modifying these identified predictors.