ABSTRACT Aims Specific leaf area (SLA), the ratio of leaf surface area to dry mass, is a key functional trait widely used to characterize resource allocation to light interception in plants. However, inconsistencies in SLA measurement—particularly whether petiolar tissues (such as petioles and rachises) are included—could lead to discrepancies in SLA estimates, especially in woody plants with compound leaves. This study investigates how two SLA measurement protocols (including vs. excluding the petiolar component) affect SLA estimates in both simple and compound leaves, with the goal of clarifying their implications for ecological studies. Location Tropical forests of the Peruvian Amazon. Methods Leaf area and dry mass were measured in 2758 individuals representing 1054 woody plant species from three sampling areas. We evaluated differences in the relationship between leaf area and dry mass across leaf types and measurement protocols while controlling for species‐level variation and phylogenetic structure. Additionally, a literature review was conducted to evaluate prevailing SLA measurement practices. Results Compound leaves exhibited consistently higher SLA than simple leaves of similar size, regardless of the protocol, with differences increasing with leaf size. Excluding the petiolar component amplified the disparity between leaf types, while SLA estimates for simple leaves remained relatively consistent across protocols. SLA declined with increasing leaf area in all cases. The literature review revealed that 46.8% of studies did not specify SLA measurement protocols, and among those that did, 76.2% included the petiolar component. Conclusions SLA measurement protocol substantially influences trait estimates, particularly for compound leaves. While the protocol choice should be guided by the specific goals of each study, we argue that a default approach incorporating both laminar and petiolar components is optimal, as it is cost‐effective and easy to implement. Clear methodological reporting is essential for ensuring comparability across studies and advancing the use of SLA in plant ecological research.