Background : Randomized clinical trials are the gold-standard for generating high-quality medical evidence, but patient recruitment remains one of the most important barriers to their success despite significant administrative effort and money being spent to address this problem. While previous studies have highlighted key trial design characteristics, such as trial phase, trial sponsor, and high target accrual, as important factors in why some trials fail to recruit enough patients, these studies have been limited in the number of trials analyzed and in the scope of trial characteristics considered. This work aims to thoroughly assess the association of different trial characteristics on patient enrollment in terms of recruitment rate and early termination rate on a larger scale than has been accomplished previously. Methods : This trial registration analysis collected recruitment information on clinical trials registered in ClinicalTrials.gov as well as trial characteristics from multiple additional databases (Clinical Trials Transformation Initiative, COHD.io, automatically parsed eligibility criteria). Descriptive statistics were calculated and the primary outcomes were associations of individual trial characteristics with patient recruitment rate and likelihood of early termination due to failed patient recruitment as well as variable selection using Group LASSO. Results : The trial characteristics with the strongest significant associations to patient recruitment included design variables (e.g. intervention model, allocation status, number of locations, phase, etc. ), sponsor experience (e.g. sponsor class, number of previous trials terminated due to recruitment issues, ratio of terminated trials to completed trials, etc. ), eligibility criteria (e.g. number of inclusion criteria, number of exclusion criteria), and trial competition (e.g. overlapping eligibility criteria, similar trials within 100 miles, etc. ). Different disease categories also showed different recruitment efficacy. Conclusions : When designing clinical trials, special attention should be paid to design variables, sponsor trial experience, eligibility criteria, and trial competition to balance the likelihood of successful recruitment against evidence strength. Further research is needed to identify causal variables and improve the predictive power of patient recruitment rates to increase the breadth of this analysis.