We aimed to identify effect sizes of age discrimination in recruitment based on evidence from correspondence studies and scenario experiments conducted between 2010 and 2019. To differentiate our results, we separated outcomes (i.e., call-back rates and hiring/invitation to interview likelihood) by age groups (40-49, 50-59, 60-65, 66+) and assessed age discrimination by comparing older applicants to a control group (29-35 year-olds). We conducted searches in PsycInfo, Web of Science, ERIC, BASE, and Google Scholar, along with backward reference searching. Study bias was assessed with a tool developed for this review, and publication bias by calculating R-index, p-curve, and funnel plots. We calculated odds ratios for callback rates, pooled the results using a random-effects meta-analysis and calculated 95% confidence intervals. We included 13 studies from 11 articles in our review, and conducted meta-analyses on the eight studies that we were able to extract data from. The majority of studies were correspondence studies (k=10) and came largely from European countries (k=9), with the rest being from the U.S. (k=3) and Australia (k=1). Seven studies had a between-participants design, and the remaining six studies had a within-participants design. We conducted six random-effects meta-analyses, one for each age category and type of study design and found an average effect of age discrimination against all age groups in both study designs, with varying effect sizes (ranging from OR = 0.38, CI [0.25, 0.59] to OR = 0.89, CI [0.81, 0.97]). There was moderate to high risk of bias on certain factors, e.g., age randomization, problems with application heterogeneity. Generally, there’s an effect of age discrimination and it tends to increase with age. This has important implications regarding the future of the world’s workforce, given the increase in the older workforce and later retirement.