Background: Predictive Models are an important tool in event predicting and health planning. Despite this, there are few works focusing this area. Thus, the analysis of the real benefits of these models in Health Sciences is necessary to be performed. Results:Predictive techniques largely evolved in second half of XX century. The development of AR, MA, ARMA, ARIMA and SARIMA models, through Box-Jenkins methodology, constitute a robust conjunct of mechanisms able to help in solution of epidemiological modeling problems, mainly in Health Sciences, once it allows to evaluate individual characteristics of living beings and its correlation with pathologies in the same space-time. Nevertheless, AR, MA and ARMA does not have tendency in seasonality, which weakens the analysis. Conclusions:To predict the natural history of endemic/epidemic and its health-disease processes in a determined population is a sine que non condition to its adequate management in Public Health context and in adoption of affirmative measures concerning health promotion. Thus, the predictive models, with emphasis in ARIMA, SARIMA, Artificial Neural Networks and Formalism of Copulas are alternatives that can be feasible.Preditive Models and Health Sciences: a Brief Analysis

Introduction: Despite variations in the beginning and the end, adolescence is the second decade of life, 10-19 years. According to the World Report on disability among those individuals aged 0-14 years of age, 93 million had severe or moderate disabilities and 13 million severe disabilities. Therefore, this study aimed to identify adolescents with hearing, visual and physical impairment. Methods:A quantitative transversal study of a medium-sized municipality. Data was collected at interviews conducted by community health workers, with an instrument containing sociodemographic data and impairment characteristics. Data was organized in spreadsheets and analyzed for correlations between types of disabilities and other variables by chi-square test. Statistical significance was verified by a 0.05 level.Results: Physical disability prevailed over visual and auditory. An association was found between disability and level of education (p = 0.023). Conclusion: Support and incentive education policies are necessary among the disabled.