This study examines how cone penetration test (CPT) parameters, such as cone tip resistance and friction sleeve resistance, can be used to assess the compressibility of fine-grained soils across the Netherlands based on a database of 286 paired CPTs and oedometer tests from across the country. This is done with the aim of refining and simplifying the parameterisation of the Koppejan consolidation coefficients, a procedure which can yield significant error and is prone to misinterpretation. It was found that there is significant potential
in using gradient boosting methods to obtain a relationship between the CPT parameters and the Koppejan parameters, with further investigation required into the noise within the dataset and the acquisition of additional high-quality samples. The use of such methods will offer a means of reducing the influence of human error or misinterpretation on the prediction of settlement and provide further confidence in the use of machine learning methods in engineering practice