Objective: To construct a new model for predicting the outcomes and therapeutic efficacy of colorectal cancer (CRC). Methods: Firstly, univariate and LASSO-Cox regression analysis were used to train cohort GSE39582 to construct a prognostic signature of colorectal cancer (PSCRC), and external cohorts CRC_TCGA and GSE17536 were used to validate PSCRC. Then, the correlation between PSCRC and clinical indicators, immune microenvironment (TME) and immune cells infiltration was evaluated, and the molecular function of PSCRC was analyzed by Gene set enrichment analysis (GSEA). Next, 7 factors including PSCRC and clinical stage were integrated to draw a prognostic nomogram, and the prognostic effect was evaluated by decision curve analysis (DCA). Finally, the efficacy of immunotherapy and chemotherapy was predicted. Results: We constructed a prognostic signature PSCRC, and two external cohorts confirmed its high prognostic sensitivity and specificity. TNM stage significantly affected the PSCRC riskscore (all p < 0.001); PSCRC was significantly positively correlated with TME StromalScore, ImmuneScore and ESTIMATEScore (all p < 0.001), significantly positively correlated with neutrophil and other cells (all p < 0.05), and significantly negatively correlated with T cell CD4+ memory activated and other cells (all p < 0.01). In addition, GSEA analysis indicated that PSCRC may participate in oxidative phosphorylation, angiogenesis, hypoxia and inflammatory response. Moreover, the newly constructed model showed good prognostic ability (C-index: 0.765, 95% CI (0.747-0.783), p < 0.001). Finally, the therapy prediction results showed that the low-risk scoring group had a higher response rate to immunotherapy (p < 0.001, p < 0.001, p = 0.08); PSCRC was significantly negatively correlated with the half inhibitory concentration (IC50) of imatinib, dasatinib, pazopanib and other drugs (all p < 0.001), and significantly positively correlated with the IC50 of metformin, sorafenib and other drugs (all p < 0.001). Conclusion: We constructed a prognostic signature PSCRC, which provides a good model for CRC prognosis and also a potential marker for predicting treatment.