Sepsis-induced coagulopathy (SIC) is a common cause of poor prognosis in critically ill patients in the intensive care unit (ICU). This study aimed to develop a predictive nomogram incorporating clinical markers and scoring systems to individually predict the probability of SIC in septic patients. Patients consecutively recruited in the stage between January 2022 and April 2023 constituted the development cohort for retrospective analysis to internally test the nomogram, and patients in the stage between May 2023 to November 2023 constituted the validation cohort for prospective analysis to external validate the nomogram. The nomogram was validated in an independent external validation cohort, involving discrimination and calibration. A decision curve analysis was also performed to evaluate the net benefit of the insertion decision with this nomogram. A total of 548 and 245 patients were included in the development and validation cohort, respectively. Predictors contained in the prediction nomogram included shock, platelets and INR. Patients with shock (OR, 4.499; 95% CI, 2.730-7.414; P < 0.001) , higher INR (OR, 349.384; 95% CI, 62.337-1958.221; P < 0.001) and lower platelet (OR, 0.985; 95% CI, 0.982-0.988; P < 0.001) had higher probabilities of SIC. The development model showed good discrimination, with an AUROC of 0.879(95%CI, 0.850-0.908)and good calibration. Application of the nomogram in the validation cohort also gave good discrimination with an AUROC of 0.872(95%CI,0.826-0.917)and good calibration. By incorporating shock, platelets and INR in the model, this useful nomogram could be accessibly utilized to predict SIC occurrence in septic patients.