The present paper proposes a novel approach for the representation of the imperfect plate geometry of ships structures and assess its impact on the probabilistic ultimate strength of plates and hull-girders. The description of the imperfect geometry is basically implemented using the theory of random fields. Evidence for the selection and robustness of the proposed model is documented from literature data and real measurement campaigns conducted on ships. A preliminary study is first presented upon the prediction of plates’ probabilistic ultimate strength comparing the efficiency of the proposed model with existing imperfection models from literature. Afterwards, a case study on a VLCC oil tanker for the prediction of hull-girder ultimate strength applying different imperfection models takes place. In order to evaluate the variability of ultimate strength under the effect of stochastic imperfections, artificial neural networks (ANNs), which trained appropriately with relatively limited results of non-linear finite element calculations, are used. The main objective of this research study is to provide a methodology for the evaluation of probabilistic-based ultimate strength assessment of plates and hull-girders in view of stochastic geometric imperfections. In doing so, and incorporating other sources of uncertainties, the designer/engineer should be able to perform a valuable reliability-based analysis of the structure. •A newly proposed probabilistic-based imperfection model is introduced via the spectral representation method.•The impact of stochastic geometric imperfections on the ultimate strength of plates is assessed.•ANNs are used to predict the stochastic hull-girder ultimate strength replacing the time-consuming NLFEA.