Central limit theorem helps us understand the features of 'population of the means' that have been generated from the mean of infinite numbers of random population sample of size. Each of them drawn from the given 'parent population'. Normal distribution curve is handy in computing the probabilities related to continuous variables which are normally distributed. Central Limit theorem asserts that the sampling distributions of large sample size are approximately normal, even if the population distribution itself is not normal. This answers the question about sample means and allows normal distribution to be used to find the probabilities of individual values in the samples.