In the last ten years, the United States has focused on the investment in high speed rails. With existing high speed rails (HSRs) and plans on reinvesting in high speed rail infrastructure, accurate planning and assessments are critical to make sure that these investments are spent wisely. Traditionally the investment in high speed rails is characterized by the infrastructure cost, operation and maintenance cost, and the overall revenue from ridership and savings. Studies have shown, that though these cost are accurate in determining the financial feasibility of high speed rails, the identified factors do not indicate the entire scope or potential of high speed rails. Additional factors should be utilized in determining whether HSRs are successful or not. The point of this research is to investigate additional factors of HSRs including time, population, the connection to economic markets, and the overall presence of HSR lines in a specific area in order to understand the significance of HSRs and to provide a platform on whether potential HSRs will be successful predicated off historical data. The net income or profit will be the determining factor on whether HSRs are successful or not being that this is the major concern on justifying the initial investment in HSRs. A regression model is utilized in order to determine whether investing in HSRs will be successful, by utilizing historical data of existing HSRs. This data shows the correlation between the noted factors (time, population, economic markets and track miles) and the profitability of existing HSRs.