Abstract: Cone penetration testing (CPT) is commonly used to evaluate sand liquefaction potential due to its efficient and reliable merits. The typical CPT method Chinese code method shows unreasonable results in fine-grained and deep soils, and the results are difficult to be integrated into probabilistic risk assessments. In this study, a novel CPT hyperbolic probabilistic model is proposed to improve the Chinese code methods based on the Bayesian weighted maximum likelihood estimation by considering the effects of fines content, uncertainties and sampling bias. The critical cone tip resistance corresponding to PL=15% is recommended as the deterministic method. Examples are presented to illustrate the reliability of the proposed method. Results show that the critical cone tip resistance of the CPT hyperbolic model increases with the increase of depth, and tends to be stable gradually, which can better reflect the dynamic characteristics of soil. The model can be applied to deep-depth and high fines content soils, and the performance is better than Chinese code method and widely used Robertson and Wride method. In sites with high uncertainty, probabilistic models can be used as an alternative or supplement to deterministic models.