Purpose: To demonstrate the feasibility of improving prostate cancer patient outcomes with PBS proton LET_d optimization. Methods: SFO, IPT-SIB, and LET-optimized plans were created for 12 patients, and generalized-tissue and disease-specific LET-dependent RBE models were applied. The mean LET_d in several structures was determined and used to calculate mean RBEs. LET_d- and dose–volume histograms (LVHs/DVHs) are shown. TODRs were defined based on clinical dose goals and compared between plans. The impact of robust perturbations on LET_d, TODRs, and DVH spread was evaluated. Results: LET_d optimization achieved statistically significant increased target volume LET_d of ~4 keV/µm compared to SFO and IPT-SIB LET_d of ~2 keV/µm while mitigating OAR LET_d increases. A disease-specific RBE model predicted target volume RBEs > 1.5 for LET-optimized plans, up to 18% higher than for SFO plans. LET-optimized target LVHs/DVHs showed a large increase not present in OARs. All RBE models showed a statistically significant increase in TODRs from SFO to IPT-SIB to LET-optimized plans. RBE = 1.1 does not accurately represent TODRs when using LET_d optimization. Robust evaluations demonstrated a trade-off between increased mean target LET_d and decreased DVH spread. Conclusion: The demonstration of improved TODRs provided via LET_d optimization shows potential for improved patient outcomes.