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            <funder>This work has received funding from the European Union's Horizon 2020 research andinnovation program under the REMAP project (grant agreement number 769288).https://h2020-remap.eu/</funder>
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              <p>Thanks to their high strength to mass ratio, composite materials arenow widespread in the aerospace industry. Nevertheless, this type of material is sub-ject to internal damages like delamination. In order to detect and localize thesedamages, robust and precise Structural Health Monitoring algorithms exist for thispurpose and have been validated experimentally. However, in order to avoid struc-tures catastrophic failures and to estimate their residual life, there is still a huge needof reliable damage size assessment methods. In this paper, a damage quanti cationmethod is proposed. This strategy is based on the extraction of a damage size sen-sitive feature computed from damage imaging results. Here damage imaging standsfor methods that use ultrasonic Lamb waves-based map of damage localization like-lihood index. This feature is extracted from each labelled example of a training setin order to infer a mathematical model used to predict the area of a delamination ofunknown damages. The proposed method is successfully validated on experimentaldata carried out on CFRP plate samples equipped with a piezoelectric transducersnetwork.</p>
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