Climate change is very likely to impact on oi l palm productivity and raise new questions on how to tackle these changes. The development of new strategies to find more sustainable and productive systems is a major challenge to cope with ceaseless increasing demands of palm oil. Agronomic practices or the selection of genetic material better adapted to future climate could be an option to maintain the high productivity of oil palm. The evaluation of plant and system performances related to climate change is nevertheless difficult to implement, particularly with perennial plants. Functional-structural plant mode ls (FSPM) have been developed to explore the relationships between plant structure, plant functioning and environmental conditions. FSPM are thus practical tools to set up virtual experiments and test hypotheses concerning processes that could otherwise take years in actual field conditions. The main assumption underlying this project is the possibility to enhance potential crop production optimizing plant architecture in relation to radiation us e efficiency. In this way, the present study proposes the basis of an oil palm FSPM, focusing on modelling oil palm architecture and light interception. A modelling approach has thus been developed to reconstruct oil palm architecture from simple field measurements while integrating the genetic variability observed on 5 progenies with contrasting genetic origins. The AMAPstudio software (Griffon & de Coligny, 2014) was used to generate 3D mock- ups and estimate light interception efficiency on virtual plants for each progeny. Model evaluation was performed using terrestrial laser scan (TLS) and hemispherical photographs (HPs) to compare the quality of 3D reconstruction respectively at the individual and stand scale. Significant differences in leaf geometry (petiole length, density of leaflets and rachis curvature) and leaflets morphology (gradients of leaflets length and width) were detected between and within progen