This　paper　proposes　an　adaptive　β-order　Minimum-Mean-Square-Error　(MMSE)　estimator　for　speech　enhancement　using　super-Gaussian　speech　model　(β-SG-MMSE).　The　spectral　amplitude　of　clean　speech　is　estimated　by　MMSE　estimator　under　the　assumption　that　the　DFT　coefficients　of　clean　speech　are　modeled　by　super-Gaussian　distribution　and　the　DFT　coefficients　of　noise　signal　are　modeled　by　Gaussian　distribution.　Then,　the　speech　presence　probability　under　super-Gaussian　model　is　introduced　into　the　proposed　estimator.　In　order　to　obtain　a　good　trade-off　between　noise　suppression　and　speech　distortion,　the　order　β　of　estimator　is　updated　adaptively　according　to　the　Signal-to-Noise　Ratio　(SNR)　in　each　sub-band.　The　result　of　performance　evaluation　by　ITU-T　G.160　shows　that　the　overall　performance　of　the　proposed　method　is　better　than　the　reference　algorithms　in　white　noise　and　color　noise.　©　2013　IEEE.