Introduction: The aim of this study was to create a model for the identification of a perforated appendicitis. Patients and Method:All consecutive patients who have undergone an appendectomy in the DY Patil Medical Hospital, Pune between January 1, 2015 and July 31, 2017 were included in a retrospective cohort study. Baseline patient characteristics, history and laboratory data were collected. Variables discriminating perforated from non-perforated appendicitis were identified using univariate and multivariable analyses. These items were used to create a model to predict perforation.Results: A total of 498 patients were included in the study. In the univariate analysis leukocyte count (LC), C-Reactive Protein levels (CRP), Erythrocyte Sedimentation Rate levels (ESR), days of symptoms and temperature were identified as predictors of perforated appendicitis. A predictive model was created using CRP, LC, ESR, duration of abdominal pain, and temperature. The predicted probability (P) of a perforated appendicitis can be calculated from the following model: (P) = 1 / (1+e (-(-2.788 + 0.012* CRP + 0.207* days with complaints))). Conclusion:Perforation of appendicitis can be predicted from the CRP level and the duration of abdominal pain. These findings might influence the choice between conservative or surgical treatment of appendicitis, and could provide guidance in the early start of antibiotics. Keywords: