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Optical remote sensing provides information on important vegetation variables such as leaf area index (LAI), biomass, and chlorophyll content. In this study, rice crops, which are rarely studied, were selected because of their high economic importance and the role they play in food security in the study area. The aim was to obtain a reliable estimate of canopy chlorophyll content as an important indicator for the evaluation of the plant status. PROSAIL radiative transfer model and the multispectral image data of ALOS AVNIR-2 were used. A field campaign was carried out in July 2010 in the northern part of Iran, Amol. Sixty sample plots of 20 × 20 m-2 were randomly selected, and their chlorophyll content was measured using a SPAD-502 chlorophyll meter. The PROSAIL was inverted using a lookup-table (LUT) approach. The LUTs were generated in different sizes. The effect of the LUT size on the retrieval accuracy of the canopy's chlorophyll content was studied using analysis of variance (ANOVA). The outcome of the inversion was evaluated using the calculated R2 and RMSE values with the field measurements. The obtained results demonstrate the ability of PROSAIL to estimate rice plant chlorophyll content using ALOS AVNIR-2 multispectral data (R2= 0.65; RMSE = 0.45). The results also confirmed the usefulness of such an approach for crop monitoring and ecological applications.