The last two decades have seen a dramatic increase in randomized controlled trials (RCTs) conducted in community colleges. Yet, there is limited empirical information on the design parameters necessary to plan the sample size for RCTs in this context. We provide empirical estimates of key design parameters, discussing lessons based on the pattern of estimates across outcomes, semesters, and studies. Nearly all RCTs in community colleges use student random assignment within blocks (colleges or cohorts). Key design parameters for the minimum detectable true effect (MDTE) are the within-block outcome standard deviation ([sigma][subscript ¦][subscript S]) and the within-block outcome variance explained by baseline covariates like student characteristics (R[superscript 2][subscript ¦][subscript S). The main analyses use student-level data from 8 to 14 RCTs including 5,649-7,099 students (depending on the outcome) with follow-up data for 3 years. A public database created for this paper includes parameter estimates for 30 RCTs including 65,637 students. Enrollment, credits earned, credential attainment, and grade point average. The within-block standard deviation ([sigma]jS) and therefore the MDTE can be much larger in later semesters for enrollment outcomes and cumulative credits earned. There is substantial variation across studies in [sigma][subscript ¦][subscript S] for degree attainment. Baseline covariates explain less than 10% of the variation in student outcomes. When planning the sample size for a study, researchers should be mindful of the follow-up period, use a range of values to calculate the MDTE for outcomes that vary across studies, and assume a value of R[superscript 2][subscript ¦][subscript S] between 0 and 0.05. [This is the online first version of an article published in "Evaluation Review."]