In an effort to understand conditions triggering asthma episodes and therefore create a asthma risk index that might be valuable to both patients and medical practitioners, 6 different counties in Florida were chosen, 3 of them in the southeast region and 3 located in the central region. The number of cases at emergency rooms due to asthma and other respiratory conditions were provided by the Department of Health BRACE project and analyzed statistically looking for potential associations with weather and environmental conditions. Weather information was obtained from airports through Wolfram Language data mining interface, and environmental parameters (Ozone level and particulate matter) from the Environmental Protection Agency measuring stations. Correlation analysis was performed with both, linear and logistic models and using software RStudio. Additionally, ARIMA forecasting modeling was implemented within RStudio to predict future events based on previous records and compared with a Machine Learning approach.