A Probability Mass Function (PMF) is a fundamental concept in probability theory that describes the distribution of discrete random variables. It provides a mapping from each possible outcome of a random variable to its corresponding probability, ensuring that the total probability across all outcomes sums to one. For example, when rolling a fair six-sided die, the PMF assigns a probability of 1/6 to each outcome (1 through 6). PMFs are essential for calculating probabilities in various applications, such as statistics, machine learning, and decision-making processes, allowing us to understand and predict the behavior of discrete systems.