Hydrothermal carbonizationHydrothermal carbonization is a process that converts biomass into a form of charcoal, offering an environmentally friendly way to reduce our reliance on natural resources and lower \(\text {CO}_{2}\) emissions that contribute to global warming. However, understanding this process can be difficult due to its complexity and the many variables involved. To simplify this, this chapter uses a powerful machine learning tool called the extreme gradient boosting to predict important characteristics of the resulting hydrochar. These characteristics include how much hydrochar is produced, its energy content, ash content, and its composition of carbon, hydrogen, and oxygen. By analyzing a large dataset with over 1,000 data points and 16 different input factors, the predictions were very accurate, with strong correlations between the predicted and actual values. Furthermore, this chapter examines how different input factors affect these characteristics using advanced methods like Shapley values and SHAP dependence plots. This analysis provides valuable insights into the process and showcases an innovative approach, contributing significantly to the field.