Objective: Studying the prognosis of breast cancer (BRCA) is of great significance for clinical treatment. LncRNA has been shown to be significantly important in breast cancer, but only few studies exist that relate to the prognosis of lncRNA. This study aimed to build a lncRNA-based breast cancer prognosis risk model using the data from TCGA datasets. Methods: we used the TCGA public database to explore the differential expression of lncRNA and cancer prognosis in breast cancer patients. The RNA-Seq data and clinical data pertaining to 1090 BRCA patients in the TCGA database were downloaded and analyzed. The prognosis-related lncRNAs in BRCA patients were identified in the training set and validated in the test set and the complete data set. ROC was performed to determine the optimal cut-off point for patient risk classification, and survival analysis was performed to determine its significance in prognosis prediction. Results: A total of 19 prognosis-associated differentially expressed lncRNAs (LSINCT5, TRG-AS1, CH17-189H20.1, RP11-1399P15.1, RP11-344P13.6, RP5-1028K7.2, AL022344.7, USP30-AS1, RP11-522I20.3, AL122127.25, BHLHE40-AS1, CHRM3-AS2, LINC00704, RP5-1073O3.2, RP11-316M21.6, CTA-384D8.31, RP11-10J5.1, RP11-426L16.3, RP11-344B5.2) were screened out. The BRCA prognosis risk assessment model based on 19-lncRNA can predict the survival rate of breast cancer patients. Conclusion: This model can predict the prognosis of breast cancer patients and these 19 lncRNAs can be used as potential molecular markers for breast cancer prognosis prediction.