Many people facing life difficulties are unable to sort out these problems. Objectives: A study was designed to determine students' life skills at the Iran University of Medical Sciences (IUMS). Methods: This cross-sectional study was conducted at IUMS in 2016 -17 with a sample of 342 students. A questionnaire was used with multi-choice questions from poor to high skills. Latent class models were applied for data analysis using Mplus. Bayesian information criterion (BIC) and Bootstrap

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... ratio tests were used to determine the number of classes. Results: A two-class model had the best fit since the BIC had the lowest amount. Almost 76% and 24% of the cases entered the high and moderate skill classes of the model, respectively. The level of education (LOE) was the only significant variable (P = 0.004) for classifying the students. Conclusions: The model could predict the probability of high life skilled students. Also, LOE had a high impact on the probability of high life skills.