The Least Squares Calculator determines the best-fit line for a dataset by minimizing the sum of squared residuals between observed and predicted values. The resulting slope indicates the rate of change of Y with respect to X, while the intercept shows the expected Y value when X is zero. This approach is widely used in regression analysis for modeling relationships and making predictions.