There are various terms and often a synonym for the concept in the statistical literature. These terms include missing values, missing data, incomplete and unanswered data. But what must be considered, it is missing data is much better than wrong answers in the data. Each method that we use to analyze the missing data has the weaknesses and strength which depends on the factors such as the ratio and missing pattern, type and number of used variables, missing mechanism. Statistically, some missing data are completely independent from the data which has been observed yet, this data are called “Missing Completely at Random”. In some cases, missing values are also “Missing at Random” and they are provided by a number of variables or data predictive class. Another set of missing data is considered “No Ignorable Missing Data”. Many researchers have provided ways to deal with the problem of missing data.