Bioluminescence　tomography　(BLT)　is　becoming　a　promising　tool　because　it　can　resolve　the　biodistibution　of　bioluminescent　reporters　associated　with　cellular　and　subcellular　function　through　several　millimeters　with　to　centimeters　of　tissues　in　vivo.　However,　BLT　reconstruction　is　an　ill-posed　problem.　By　incorporating　sparse　a　priori　information　about　bioluminescent　source,　enhanced　image　quality　is　obtained　for　sparsity　based　reconstruction　algorithm.　Therefore,　sparsity　based　BLT　reconstruction　algorithm　has　a　great　potential.　Here,　we　proposed　a　novel　reconstruction　method　based　on　Bayesian　compressive　sensing　and　investigated　its　feasibility　and　effectiveness　with　a　heterogeneous　phantom.　The　results　demonstrate　the　potential　and　merits　of　the　proposed　algorithm.