Objective: To develop and externally validate a risk score to predict post-operative Acute Kidney Injury (AKI) in patients undergoing orthopaedic surgery and to examine the impact of AKI on both short and long term survival. Design: Observational Cohort Setting: Scotland, United Kingdom (UK). Participants: All adults over 18 years who underwent orthopaedic surgical procedures from 1st January 2005 to 31st December 2011 who were resident in the National Health Service (NHS) Tayside region of Scotland. Main Outcome Measures: AKI within the first seven post-operative days in patients undergoing orthopaedic surgery, and ninety day, one year and survival until end of follow-up. Results: The model was developed in 6220 patients (from 2 hospitals) and externally validated in 4395 patients from a third hospital. Logistic regression analysis showed that older age, male sex, presence of diabetes, number of preadmission medicines, higher baseline creatinine, use of ACE inhibitors or angiotensin receptor blocker and American Society of Anesthesiologists grade were independent predictors of AKI. These were included in the prediction model which had good predictive performance, with a c-statistic of 0.74 (95%CI 0.72 to 0.76) in the derivation cohort and 0.70 in the validation cohort. Survival in patients with AKI was worse compared to patients without AKI: adjusted HR 1.53 (1.38 to 1.70, p<0.0001). This was most striking in the short term: adjusted 90 day HR 2.36 (95%CI 1.94 to 2.87, p<0.0001) and diminished over time: 90 day-1 year adjusted HR 1.40 (1.10 to 1.79, p=0.007); >1 year adjusted HR 1.28 (1.10 to 1.48, p=0.001). Conclusions: AKI affects up to 11% of patients undergoing orthopaedic surgery with increased longer term mortality even with milder forms of AKI. We have developed and externally validated a pre-operative risk prediction model identifying seven predictors for AKI in patients undergoing orthopaedic surgery which we have translated into a simple spread sheet. Early identification and prevention of AKI has the potential to lead to improved post-operative outcomes worldwide. UK Clinical Research Network ID Number: 17650.