Abstract Background: Less than 10 % of those identified as eligible for clinical trials are recruited. Recruitment for chemoprevention trials poses challenges as it is often difficult to identify unaffected patients at high risk for cancer. Barriers to recruitment include personal perceptions of the benefits, fear of trials, low recruitment of minorities, language barriers, transportation costs, and complex study designs. In this study, we identified five potential sources of recruitment that could be collectively leveraged to identify women at high risk for breast cancer to improve recruitment yield. Methods: A total of 300 high-risk women and 50 healthcare providers were recruited and randomized to access web-based decision support tools in combination with standard educational materials or standard educational materials alone. Patient inclusion criteria included: 1) women, age 35-75 years; 2) English or Spanish-speaking; 3) no previous breast cancer diagnosis; 4) no prior use of selective estrogen receptor modulators (SERMs) or aromatase inhibitors (AIs). Five broad strategies were considered for identification and recruitment of women at high risk for breast cancer: 1) in-person recruitment during routine screening mammography with survey administration for breast cancer risk assessment according to the Gail model; 2) collection of breast cancer risk factors from the electronic health record (EHR) for risk assessment according to the Breast Cancer Surveillance Consortium (BCSC) risk calculator; 3) identification of women with atypical hyperplasia (AH) or lobular carcinoma in situ (LCIS) using ICD-9/10 diagnostic codes from the EHR; 4) high-risk women with clinic appointments and referred by enrolled providers; 5) women who responded to recruitment flyers and online recruitment distributed throughout the medical center and community. Results: A total of 6229 high-risk women were identified using these recruitment sources, of which 3663 were contacted by email, mailed letter, and/or phone for participation in our clinical trial. Of these contacted women, 16.4% were identified through in-person recruitment during screening mammography, 35.8% through breast cancer risk factors in the EHR, 14.5% had a diagnosis of AH or LCIS identified in the EHR, 28.7% had appointments with enrolled providers, and 4.5% responded to recruitment flyers or online recruitment. Women from the different recruitment sources varied by mean age (64.7 years for mammography and 44.9 years for recruitment flyers), race/ethnicity (73.7% non-white from mammography and 45.5% from breast cancer risk factors in the EHR), and mean 5-year breast cancer risk (2.56% identified from the EHR and 1.34% from recruitment flyers). Of 300 consented patients, 44.7% came from provider referrals (12.7% recruitment yield [number consented/number contacted]) and 27.3% from mammography (13.6% recruitment yield). Comparing enrolled to unenrolled patients, there were significant differences in mean age (57.3 vs. 58.7 years, p=0.027), proportion of non-whites (41.5% vs. 54.7%, p<0.001), and mean 5-year breast cancer risk (3.0% vs. 2.2%, p<0.001). Conclusions: We were able to identify a large cohort of women at high risk from breast cancer from multiple different recruitment sources. Our recruitment yield was highest among direct referrals from healthcare providers and in-person recruitment from mammography. Consented patients tended to be younger, include more non-Hispanic whites, and have a higher risk of breast cancer compared to the overall pool of high-risk women identified. We were able to successfully recruit a racially-ethnically diverse study population to a randomized controlled trial of decision support for breast cancer chemoprevention. Citation Format: Gauri Bhatkhande, Thomas Silverman, Jennie Mata, Ashlee Guzman, Ting He, Jill Dimond, Tarsha Jones, Rita Kukafka, Katherine Crew. Recruitment strategies for enrollment of high-risk women to a randomized controlled trial of web-based decision support tools to increase breast cancer chemoprevention [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS8-11.