We cannot be sure that all samples from a normal distribution will also be normally distributed.
The Central Limit Theorem states that the sampling distribution of the sample means approaches a normal distribution as the sample size gets larger, especially for sample sizes over 30. Basically as you take more samples from a given distribution, especially large samples, the graph of the sample means will look more like a normal distribution.
However, this does not state that all samples of a normal distribution will also be normal.
