In general, several factors must be known or estimated to calculate sample size: the effect size (usually the difference between two groups), the population standard deviation (for continuous data), the desired power of the experiment to detect the postulated effect, and the significance level.
Both Merga and Jochen are correctly pointing out that any such endeavor requires consideration of a number of factors. To their comments, please allow me to add one more observation.
A basic deficiency of the one-group pre-post comparison method is that it offers so little protection against rival hypotheses (alternate explanations of why something did or did not occur, beyond the intended focus of the chosen treatment or intervention). There are many other data collection designs that offer more rigor, and thus, better protection against rival hypotheses (and other threats to the integrity and/or generalizability of the results).