Self-lubricating　bearings,　relying　on　the　intrinsic　material　properties　of　their　components,　provide　lubrication　for　relative　motion　surfaces,　allowing　them　to　be　used　in　high-end　equipment　components　such　as　aerospace,　aviation,　and　nuclear　power,　where　oil　/　grease　lubrication　is　impractical.　However,　as　high-end　equipment　components　were　pursuing　peak　performance,　new　demands　emerged　for　enhanced　reliability　and　extended　service　life　of　self-lubricating　bearings.　Therefore,　to　develop　self-lubricating　bearings　that　met　the　requirements　of　high-end　equipment　components　requires　clarifying　technologies　to　enhance　the　performance　of　existing　low-friction,　wear-resistant　self-lubricating　materials,　exploring　and　evaluating　test　methodologies　for　assessing　the　performance　of　self-lubricating　bearings,　and　mastering　predictive　techniques　for　estimating　the　lifespan　of　self-lubricating　bearings.　Based　on　this,　this　paper　introduces　the　research　progress　of　three　typical　self-lubricating　bearing　mechanisms,　elucidates　the　life　testing　instruments　for　both　rotating　and　sliding　self-lubricating　bearings,　summarizes　three　methods　for　predicting　the　lifespan　of　self-lubricating　bearings　based　on　statistics,　physical　models,　and　machine　learning.　Finally,　this　paper　analyzes　and　forecasts　future　research　directions　for　self-lubricating　bearings.　©　2025　Cailiao　Daobaoshe/　Materials　Review.　All　rights　reserved.