Background and Aims Gallbladder squamous cell carcinoma (GSCC) is a rare histopathological subtype of gallbladder cancer, accounting for 1% to 4% of cases. This tumor type is associated with poor prognosis. Currently, the literature on GSCC mainly consists of case reports and small-sample case series. Due to the lack of large-sample high-quality clinical research evidence, there are no established treatment guidelines, consensus, or personalized prognostic assessment tools for GSCC. Therefore, this study aimed to construct prognostic nomograms for GSCC patients using large-scale real-world data from the SEER database to provide precise and individualized prognosis assessment for GSCC patients, offering valuable references for clinical decision-making.Methods Clinical data of GSCC patients pathologically diagnosed between 2000 and 2019 were extracted from the SEER database. The data were randomly divided into training and validation sets in a 7∶3 ratio. In the training set, a multivariate Cox proportional hazards model and LASSO regression were used to identify independent prognostic factors for the survival of GSCC patients. These factors constructed nomogram models to predict tumor-specific survival (CSS) and overall survival (OS) at 3 and 6 months for GSCC patients. Subsequently, the models were internally and externally validated in training and validation sets using the concordance index (C-index), ROC, and calibration curves to assess their accuracy and predictive capacity.Results A total of 257 patients were included in this study, 179 in the training and 78 in the validation set. The median follow-up times were 3 (1-7) months in the training set and 4 (2-8) months in the validation set. Baseline characteristics were comparable between the two groups. The multivariate Cox proportional hazards model analysis revealed that age, SEER stage, surgery, and chemotherapy were independent factors for OS and CSS in GSCC patients (all P<0.05). LASSO regression analysis indicated that age, SEER stage, radiotherapy, surgery, and chemotherapy were associated with OS; age, SEER stage, surgery, and chemotherapy were correlated with CSS in GSCC patients. Nomograms for predicting OS and CSS at 3 and 6 months were developed based on these independent prognostic factors. Validation results demonstrated C-index values of 0.739 (95% CI=0.700-0.780) and 0.729 (95% CI=0.660-0.800) for OS in the training and validation sets, respectively; C-index values of 0.750 (95% CI=0.710-0.790) and 0.741 (95% CI=0.670-0.810) for CSS in the same sets. ROC curve analysis indicated AUC values >0.8 in both training and validation sets. Calibration curve analysis showed good agreement between predicted and actual OS and CSS at 3 and 6 months for GSCC patients. Both were closely situated near the ideal 45° reference line, demonstrating high consistency.Conclusion Age, SEER stage, surgery, radiotherapy, and chemotherapy are independent prognostic factors for GSCC patients. The constructed nomogram prediction models exhibit favorable predictive value and facilitate personalized treatment selection for GSCC patients in the clinical setting.