Benford's Law is a statistical principle that predicts the frequency distribution of the first digits in many real-life sets of numerical data. According to this law, smaller digits, particularly the number 1, appear as the leading digit more often than larger digits. For example, about 30% of the numbers in a dataset will start with the digit 1, while only about 4.6% will start with the digit 9. This phenomenon occurs in various fields, including finance, demographics, and scientific data. It can be used to detect anomalies or fraud, as deviations from this expected distribution may indicate manipulation. Fraud detection and data analysis often utilize Benford's Law to identify irregularities.