Abstract: The in situ behaviour of pile foundations is considerably influenced by variability in soil properties. Cone penetration (CPT) data are often used to determine the pile ultimate capacity. A wider range of values of the ultimate capacity are predicted when different CPT-based methods are used, as compared to using pile load test results. The present study considers inherent soil variability, measurement, and transformation variability. The undrained shear strength obtained from CPT data is considered to be a random variable. An approach to obtain load–settlement curves and the associated statistics from CPT data is suggested. Component reliability indices, based on ultimate limit state (ULS) and serviceability limit state (SLS) criteria, and system reliability indices combining ULS and SLS are evaluated. The variability in the pile–soil interface parameters and pile ultimate capacity is quantified in a Monte Carlo framework using the measured data. The effects of variability, scale of fluctuation, and limiting serviceability settlement on the reliability of pile foundations are also examined. A geotechnical database from the Konaseema site in India is utilized as an example. It is shown that the reliability based design of pile foundations considering spatial variability of soil, along with the variables associated with pile–soil interface properties, enables a rational choice of design loads
