Cuproptosis, a newly identified form of cell death, has drawn increasing attention for its association with various cancers, though its specific role in colorectal cancer (CRC) remains unclear. In this study, transcriptomic and clinical data from CRC patients available in the TCGA database were analyzed to investigate the impact of cuproptosis. Differentially expressed genes linked to cuproptosis were identified using Weighted Gene Co-Expression Network Analysis (WGCNA). Key genes were further refined through LASSO regression and random forest approaches, culminating in the development of a prognostic model comprising six critical genes. The predictive accuracy of the model was validated using two independent external datasets. This model effectively stratified patients into high- and low-risk groups, which exhibited significant differences in disease stage, immune landscape, tumor mutational burden, and therapeutic response, underscoring the robustness of the model. P4HA1 was identified as a key gene of interest, where downregulation was found to inhibit tumor progression in single-cell sequencing analyses and in vitro experiments. Additionally, suppression of P4HA1 enhanced the sensitivity of CRC cells to the cuproptosis inducer elesclomol (ES), potentially through oxidative stress mechanisms. In conclusion, this study proposes a prognostic model based on six cuproptosis-related genes that could aid in personalizing CRC treatment. Furthermore, P4HA1 emerges as a promising therapeutic target.