Benford's Law is an empirical law which shows us that, in real-world data sets, low digits occur as the leading significant digit much more frequently than high digits do. It is because of this characteristic that we can use Benford's Law as a forensic test in data fraud detection. This law can also be used in other numbering systems. The applied data can be converted in different scale without changing the distribution - this is due to the fact that Benford's Law follows the invariance principle. The four foundamental numerical processes that lead to the known leading digit movement are the linear combinations of random variables process, data set aggregation process, random number selection process and the multiplication process. Before analysing, it is crucial to ensure that the data set has the widest range of data possible and that we retain only those values that are suitable for our analysis. The tests for evaluating conformity to Benford's Law include the Z-test, the chi-square test, the sum of squared deviations, Saville's linear regression analysis, the value repetition test and the digital data pattern detection method. In the end, we test the Benford's Law on the real data in Gross Fixed Capital Formation by municipalities.