The morphometric truss system is a widely used method for analyzing variations in fish body shape. However, its application remains limited for predicting standard length in specimens with incomplete body morphology. This study aims to develop a predictive model for estimating the standard length of shortfin scad (Decapterus macrosoma) based on morphometric truss characteristics as a solution for morphological estimation when fish specimens are not intact. The research was conducted at the Fisheries Science Study Program Laboratory, University of Sultan Ageng Tirtayasa. One hundred shortfin scad specimens were collected from the Karangantu Archipelagic Fishing Port (PPN Karangantu). Measurements were taken from 24 truss points, which were classified into four body regions: head (A), anterior body (B), posterior body (C), and caudal peduncle (D). The analysis employed simple and multiple linear regression, and model performance was evaluated using MAE, MSE, RMSE, and R² metrics. The multiple linear regression results indicated that the anterior body and posterior body groups exhibited the highest coefficients of determination (R² > 0.97), the lowest error values, and residuals approximating a normal distribution. In contrast, the caudal peduncle group showed the weakest predictive performance. These findings affirm that morphometric truss characteristics of the anterior and posterior body regions are the most effective quantitative indicators for predicting standard length in shortfin scad. The proposed model has significant potential to enhance the reliability of fisheries stock data, particularly under conditions involving morphologically incomplete specimens.