In　situ　fragmentation　bioleaching　is　a　promising　way　to　perform　deep　mining　safely,　economically,　and　in　an　environmentally　friendly　manner,　where　oxygen　plays　a　critical　role　in　microbial　growth　and　mineral　dissolution.　However,　the　lack　of　oxygen　limits　the　implementation　of　in-situ　fragmentation　bioleaching.　To　overcome　this　limitation,　aeration　was　proposed,　with　saturated　dissolved　oxygen　concentration　as　an　important　indicator.　Orthogonal　experiments　were　conducted　to　measure　saturated　dissolved　oxygen　concentration　at　various　temperature,　pH,　and　electrolyte　(ferrous　sulfate,　ferric　sulfate,　copper　sulfate,　and　sulfuric　acid)　concentration　conditions.　Experimental　data　were　analyzed　by　Python　programming　language　and　least　squares　method　to　obtain　a　saturated　dissolved　oxygen　concentration　model.　Results　showed　that　temperature　had　the　most　significant　effect　on　oxygen　solubility,　which　was　concluded　by　comparing　the　results　of　surface　fitting　based　on　the　least　squares　method.　At　30-40　degrees　C,　the　saturated　dissolved　oxygen　concentration　decreased　faster　as　metal　ions　concentration　increased.　The　conjoint　effect　of　the　five　variables　on　oxygen　solubility　showed　that　pH　was　linearly　negatively　related　to　oxygen　solubility.　Additionally,　a　mathematical　model　was　also　proposed　to　predict　the　saturated　dissolved　oxygen　concentration　in　in　situ　fragmentation　bioleaching　of　copper　sulfide　ores.　This　work　enables　bioleaching　processes　to　be　modeled　and　controlled　more　effectively.