Objective To establish and validate the nomogram prediction model of degenerative lumbar disc disease in young and middle-aged people. Methods From January 2020 to March 2022, 232 young and middle-aged people who were examined with MRI of lumbar intervertebral disc and standard standing position lumbar anteroposterior and lateral X-ray films in Suzhou Ninth Hospital Affiliated to Soochow University were selected as the study subjects. Collecting the factors that may affect the occurrence of degenerative lumbar disc disease in young and middle-aged people, the people were divided into degenerative disease group (n=78) and non-degenerative disease group (n=154) according to the presence or absence of degenerative lumbar disc disease. Influencing factors were compared between the two groups, the independent influencing factors screened out by multifactor logistic regression, the nomograph model was constructed by R software, and the model verified. Results Among 232 young and middle-aged people included in this study, 78 (33.6%) had degenerative lumbar disc diseases. The results of multivariate logistic regression analysis showed that the increase of BMI, sedentariness, the increase of IL-1β level were the risk factors of degenerative lumbar disc disease in young and middle-aged people; the increase of pelvic incidence angle and the increase of miRNA-142-3p level were protective factors for degenerative lumbar disc disease in young and middle-aged people (P<0.05). The nomogram model was constructed according to the results of multifactor analysis. ROC results showed that AUC was 0.889 (95%CI 0.844-0.933, P<0.05), the average absolute error of internal validation was 0.017, the prediction curve was basically fitted with the standard curve, and the H-L goodness of fit test showed that the model was consistent (P>0.05). The decision curve shows that the clinical benefit rate is the highest when the model prediction probability threshold is 0.16-0.80. Conclusions Degenerative lumbar disc disease in young and middle-aged people is affected by such factors as BMI, sedentariness, and incidence angle of pelvis, and the nomogram model established based on this has high differentiation and accuracy of prediction.