Objective To analyze risk factors for adolescent lumbar disc herniation (ALDH) and to develop a tool for quantitative assessment. Methods The clinical data and imaging data of 75 adolescent patients with ALDH (case group) and adolescent patients with low back pain but without ALDH (control group), who were treated in The First Affiliated Hospital of Naval Medical University (Second Military Medical University) from Aug. 2010 to Aug. 2021, were retrospectively analyzed. The patients were randomly divided into training set and validation set according to a ratio of 7∶3 in both groups. Age, gender, body mass index (BMI), occupation, waist trauma, smoking, lumbosacral transitional vertebra (LSTV), ratio of intercrestal line to L₅ transverse process (ICL/L₅TP), facet tropism (FT), thoracic kyphosis (TK), lumbar lordosis (LL), sacral slope (SS), and pelvic incidence (PI) were compared between the case group and control group in the training set. Logistic regression model was used to analyze the independent influencing factors of ALDH risk, and a nomogram for quantitative assessment of ALDH risk was plotted by R 4.1.3 software. The training set and validation set data were used for internal validation and external validation of the nomogram model, respectively, and the value of the nomogram model was analyzed by receiver operating characteristic curve, C index, calibration curve, and decision curve. Results Gender, BMI, occupation, waist trauma, smoking, LSTV, ICL/L₅TP, FT, LL, and SS were significantly different between the case group and control group in the training set (all P＜0.05); multivariate logistic regression analysis showed that waist trauma, smoking, BMI, ICL/L₅TP, FT, and LL were independent influencing factors of ALDH risk (all P＜0.05); and a nomogram model was established based on these 6 factors. In the training and validation sets, the nomogram model had a high predictive value for ALDH risk (AUC values of 0.980 and 0.969, respectively) with high accuracy (C indexes of 0.71 and 0.76, respectively), calibration (P＝0.562 and 0.985, respectively), and clinical benefit. Conclusion Waist trauma, smoking, BMI, ICL/L₅TP, FT, and LL are strongly associated with the risk of ALDH, and the nomogram based on these 6 factors can be used to quantitatively assess prevalence risk of ALDH.