<p>The hydrothermal solidification method offers a sustainable solution for converting waste clay into high-strength construction materials while minimizing energy consumption. Activating binding agents within the clay yields durable and weather-resistant materials, reduces energy usage and greenhouse gas emissions, and promotes waste reduction by repurposing clay waste. Its versatility allows for the production of various building materials suitable for eco-friendly construction practices. To assess the strength of hydrothermally solidified materials, 240 datasets were collected and analyzed, focusing on soil modified with calcium hydroxide Ca(OH)₂. These datasets were divided into training and testing sets for model development and validation. Variables such as Ca(OH)₂ content, water content, curing temperature, curing time, and density were considered, with compressive strength CS as the target variable. Six mathematical models, including linear, nonlinear, and quadratic forms, were employed to predict CS, with the FQ model demonstrating superior accuracy. Statistical measures revealed that the FQ model consistently outperformed others, exhibiting low objective function (OBJ) and sensitivity index (SI) values. Specifically, the FQ model achieved R² and RMSE values of 0.715 and 5.73&#xa0;MPa for training datasets and 0.827 and 5.99&#xa0;MPa, respectively, for testing datasets, indicating its reliability. Sensitivity analysis identified Ca(OH)₂ content, water content, and curing time as the most influential factors on CS, with optimal results observed at Ca(OH)2 concentrations ranging from 18 to 45%. Hydrothermal solidification’s versatility means that various eco-friendly building materials can be produced, extending the method's applicability to diverse construction needs. This could revolutionize construction practices, making them more sustainable by introducing an alternative to conventional concrete and cement products with a significant carbon footprint. Using six mathematical models to predict compressive strength (CS) demonstrates the potential for data-driven approaches to optimize material properties in construction. The superior performance of the Full Quadratic (FQ) model, with high R2 values and low RMSE, underscores the reliability and robustness of the modeling approach. These findings provide valuable insights into optimizing materials for the construction industry, where precise predictions of material properties are crucial for ensuring safety, durability, and sustainability. The sensitivity analysis provides actionable insights into the most influential factors affecting CS, namely Ca(OH)2 content, water content, and curing time. These findings enable future research to focus on optimizing these parameters, potentially leading to more cost-effective and efficient use of resources. Moreover, the optimal Ca(OH)₂ concentration range identified (18–45%) will guide practitioners in selecting the best conditions for maximizing material strength.</p>