To mitigate the societal impact of vehicle crash, researchers are using a variety of tools, including finite element models. As part of the Global Human Body Models Consortium project, comprehensive medical image and anthropometrical data of the 5th percentile female (F05) were acquired. Height, weight and 15 external anthropomorphic measurements were used to determine subject eligibility. A multi‐modality image dataset consisting of CT, MRI and upright MRI medical images was developed to characterize the subject in the supine, seated and standing postures. Surface topography and 52 bony landmarks were also acquired for model assembly. The selected subject closely represented the F05 in terms of height and weight, deviating less than 2% in those measures. For all 15 anthropomorphic measurements, the average subject deviation across all measures was 4.1%. The multi‐modality image set was used to develop and assemble skeletal and organ components of the model. Abdominal organ volumes and cortical bone thickness were compared to literature sources where data were available. The dataset used for the development of this model was acquired with the explicit purpose of developing a full‐body finite element model of the F05 for the enhancement of injury prediction.