Root Mean Square Error (RMSE) is a statistical measure used to assess the accuracy of a model's predictions. It calculates the square root of the average of the squared differences between predicted values and actual values. A lower RMSE indicates a better fit of the model to the data, meaning the predictions are closer to the actual outcomes. RMSE is commonly used in various fields, including machine learning, statistics, and forecasting. It provides a clear metric for comparing different models or algorithms, helping researchers and practitioners choose the best approach for their specific data sets and objectives.