After the World War II (WWII), the industrial era began. Therefore the risk management philosophy concerns shifted from error resolving to error prevention by predicting the causes. One of the most common processes used to decrease the failures is utilizing the Failure Mode and Effects Analysis (FMEA). FMEA approximates the probability based on Risk Priority Number (RPN). RPN is known for limitations in the process of RPN scoring system measuring the severity (S), occurrence (O), and detection of the failure (D). RPN is not an accurate, in determining the relative importance of failure. R-FMEA provides a proactive more reliable method using Kruskal-Wallis test. This article discusses with examples how a new suggested statistical model (R-FMEA) is enhancing the reliability of FMEA to predict errors.