Gumbel distribution was dealt with great care by researchers and statisticians. The Gumbel distribution, also known as the type-1 extreme value distribution, has received significant research attention, over the years particularly, in extreme value analysis of extreme events. For a review of the recent developments and applications of the Gumbel distribution, see Pinheiro and Ferrari . By approximating the size of the population, the distribution of the maximum age may be modelled by one of the asymptotic laws of extreme values. When considering the distribution of minimum values for which a lower bound is known (e.g. distribution, which can be used to describe distributions with a reverse J-shaped curve, may be more suitable than the Gumbel distribution. The Gumbel distribution is a probability distribution of extreme values. In probability theory and statistics, the Gumbel distribution is used to model the distribution of the maximum (or the minimum) of a number of samples of various distributions. It will be seen that there is considerable deviation of the data from the straight line that would represent a Gumbel distribution on a Gumbel plot. The Gumbel distribution is appropriate for modeling strength, which is sometimes skewed to the left (few weak units in the lower tail, most units in the upper tail of the strength population). In the past, if such deviation was noted, it was invariably dismissed as due to data or experimental problems or variability. The Normal distribution is symmetric; Gumbel isn't. The two distributions are closely related: if X has a Weibull distribution with parameters α and c , then log( X ) has an extreme value distribution with parameters µ=log α and β =1/ c. It is also known as the log- The Gumbel method of frequency analysis is based on extreme value distribution and uses frequency factors developed for theoretical distribution. extremes on the right side (high values) are distributed over a wider range than extremes on the low side. Compared with the Normal Distribution, Gumbel has a heavier tail. The new distribution differs in general from that describing the population. The Gumbel distribution is a specific example of the gen-eralized extreme value distribution (also referred to as the Fisher-Tippett distribution). Once the distribution is fitted properly to the observed data extrapolation to calculate required probabilities can be easily done. The Gumbel distribution could also be appropriate for modeling the life of products that experience very quick wear-out after reaching a certain age. The method utilises general equation given for hydrologic frequency analysis which is stated as below. there is a lower bound of zero) then the Weibull distribution should be used in preference to the Gumbel.