This study centers around the implementation of machine learning and predictive analytics in the generation of optimal patient appointment schedules and patient volume forecasting. GoSched utilizes two main algorithms, Genetic Algorithm (GA) and Random Forest Algorithm (RFA). GAs are mainly used by the system to model natural selection processes to search for optimal scheduling solutions under multiple constraints, while the RFA is used in aggregating predictions from different decision trees trained on bootstrapped samples to reduce overfitting and provide robust forecasts of daily appointment volumes.