| Summary: | The resurgence of interest in medicinal plants and their potential in pharmaceuticals has driven research into harnessing bioactive compounds for innovative treatments. This study proposes an accurate and non-destructive method to estimate leaf area (LA) for <i>Thevetia peruviana</i> through linear measurements of the leaf length (L), the leaf width (W), or the product of the leaf length and width (LW). The study encompasses comprehensive analyses of leaf dimensions collected during different seasons (rainy and dry season), employing linear and non-linear regression models to predict LA. Among the diverse models tested, non-linear equations emerged as superior predictors of LA, surpassing simpler linear models. However, in the rigorous selection process, the equations were linear with the intercept and power model, meeting the requirements for accurate and unbiased LA estimation. Despite the competence of these models, distinguishing between them based on evaluation criteria proved inconclusive. Following the principle of simplicity, equations linear with the intercept [LA = 0.284 + 0.766 × (LW)] are preferred as power models [LA = 0.914 × (LW)<sup>0.939</sup>] and are recommended as an optimal and practical choice for estimating <i>T. peruviana</i> LA in field experiments. The investigation emphasizes the importance of a robust approach to LA estimation, offering crucial insights into the allometric relationships and facilitating informed agricultural decisions. This comprehensive study advances our understanding of <i>T. peruviana</i> and contributes to the broader discourse on accurate and efficient leaf area estimation techniques in plant biology and agriculture.
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