To provide an overview of prediction models for the risk of major depressive disorder (MDD) among older adults. We conducted a systematic review combined with a meta-analysis and critical appraisal of published studies on existing geriatric depression risk models. The systematic search screened 23,378 titles and abstracts; 14 studies including 20 prediction models were included. A total of 16 predictors were selected in the final model at least twice. Age, physical health, and cognitive function were the most common predictors. Only one model was externally validated, two models were presented with a complete equation, and five models examined the calibration. We found substantial heterogeneity in predictor and outcome definitions across models; important methodological information was often missing. All models were rated at high or unclear risk of bias, primarily due to methodological limitations. The pooled C-statistics of 12 prediction models was 0.83 (95%CI=0.77–0.89). The usefulness of all models remains unclear due to several methodological limitations. Future studies should focus on methodological quality and external validation of depression risk prediction models. • There is still limited evidence on risk prediction models of depression among older adults. • A total of 20 models can predict the risk of developing a major depressive disorder among older adults. • All models were at high or unclear risk of bias, raising concern that their predictions could be unreliable when applied in practice. • Future studies on risk prediction models of geriatric depression should focus on improving the quality of methods. [ABSTRACT FROM AUTHOR]