Objectives: Rotator cuff tears are a common and disabling complaint. The early diagnosis of medium and large size rotator cuff tears can enhance the prognosis of the patient. The aim of this study was to identify clinical features with the strongest ability to accurately predict the presence of a medium, large or multitendon (MLM) rotator cuff tear in a primary care cohort. Methods: Participants were consecutively recruited from primary health care practices (n5203). All participants underwent a standardized history and physical examination, followed by a standardized X-ray series and diagnostic ultrasound scan. Clinical features associated with the presence of a MLM rotator cuff tear were identified (P<0.200), a logistic multiple regression model was derived for identifying a MLM rotator cuff tear and thereafter diagnostic accuracy was calculated. Results: A MLM rotator cuff tear was identified in 24 participants (11.8%). Constant pain and a painful arc in abduction were the strongest predictors of a MLM tear (adjusted odds ratio 3.04 and 13.97 respectively). Combinations of ten history and physical examination variables demonstrated highest levels of sensitivity when five or fewer were positive [100%, 95% confidence interval (CI): 0.86-1.00; negative likelihood ratio: 0.00, 95% CI: 0.00-0.28], and highest specificity when eight or more were positive (0.91, 95% CI: 0.86- 0.95; positive likelihood ratio 4.66, 95% CI: 2.34-8.74). Discussion: Combinations of patient history and physical examination findings were able to accurately detect the presence of a MLM rotator cuff tear. These findings may aid the primary care clinician in more efficient and accurate identification of rotator cuff tears that may require further investigation or orthopedic consultation.