Proteomic methodologies offer a robust approach to identify and quantify thousands of proteins from semen components in both fertile donors and infertile patients. These strategies provide an unprecedented discovery potential, which many research teams are currently exploiting. However, it is essential to follow a suitable experimental design to generate robust data, including proper purification of samples, appropriate technical procedures to increase identification throughput, and data analysis following quality criteria. More than 6000 proteins have been described so far through proteomic analyses in the mature sperm cell, increasing our knowledge on processes involved in sperm function, intercommunication between spermatozoa and seminal fluid, and the transcriptional origin of the proteins. These data have been complemented with comparative studies to ascertain the potential role of the identified proteins on sperm maturation and functionality, and its impact on infertility. By comparing sperm protein profiles, many proteins involved in the acquisition of fertilizing ability have been identified. Furthermore, altered abundance of specific protein groups has been observed in a wide range of infertile phenotypes, including asthenozoospermia, oligozoospermia, and normozoospermia with unsuccessful assisted reproductive techniques outcomes, leading to the identification of potential clinically useful protein biomarkers. Finally, proteomics has been used to evaluate alterations derived from semen sample processing, which might have an impact on fertility treatments. However, the intrinsic heterogeneity and inter-individual variability of the semen samples have resulted in a relatively low overlap among proteomic reports, highlighting the relevance of combining strategies for data validation and applying strict criteria for proteomic data analysis to obtain reliable results. This mini-review provides an overview of the most critical steps to conduct robust sperm proteomic studies, the most relevant results obtained so far, and potential next steps to increase the impact of sperm proteomic data.