Bel-W3 is an ozone-sensitive tobacco (Nicotiana tabacum L.) cultivar widely used worldwide for ozone biomonitoring. Despite its extensive use, there is no comprehensive predictive model to non-destructively estimate the leaf area using only a common ruler, yet leaf area is a major evaluative trait in plants under ozone stress and of economic value in tobacco plants. In this method, we aimed at developing a predictive model to estimate leaf area using the product between leaf length and leaf width. To this end, we conducted a field experiment with ground-grown Bel-W3 plants treated with different solutions under ambient ozone conditions. The solutions were water, the antiozonant ethylenediurea (EDU; 500 ppm), and the antitranspirant pinolene (Vapor Gard; 1%, 5%, 10%). The chemical treatments were introduced to enhance leaves pool and capture different conditions that can occur in ozone biomonitoring projects. A simple linear predictive model was developed and validated using data from a previous chamber experiment with small seedlings. Overestimation of the model led to the integration of data from both experiments and development of another simple linear predictive model. This integrated model provides improved estimation of leaf area and can be used for representative estimation of the area of Bel-W3 leaves of any sizes.