Recent advances in hyperspectral spectroscopy suggest making use of leaf optical properties for monitoring soil contamination in oil production regions by detecting pigment alterations induced by Total Petroleum Hydrocarbons (TPH). However, this provides no quantitative information about the level of contamination. To achieve this, we propose an approach based on the inversion of the PROSPECT model. 1620 leaves from five species were collected on a site contaminated by 16 to 77 g.kg(-1) of TPH over a 14-month period. Their spectral signature was measured and used in PROSPECT model inversions to retrieve leaf biochemistry. The model performed well for simulating the spectral signatures (RMSE < 2%) and for estimating leaf pigment contents (RMSE <= 2.95 mu g.cm(-2) for chlorophylls). Four out of the five species exhibited alterations in pigment contents when exposed to TPH. A strong correlation was established between leaf chlorophyll content and soil TPH concentrations (R-2 >= 0.74) for three of them, allowing accurate predictions of TPH (RMSE = 3.20 g.kg(-1) and RPD = 5.17). The accuracy of predictions varied by season and improved after the growing period. This study demonstrates the capacity of PROSPECT to estimate oil contamination and opens up promising perspectives for larger-scale applications.