To case-II waters, suspended particulate matter (SPM) is one of the dominant water constituents, SPM concentration (CSPM) is a key parameter describing water quality, and developing remote sensing-based CSPM retrieval models is foundation for obtaining its spatiotemporal distributions. This study aimed to develop moderate resolution imaging spectroradiometer (MODIS)-based CSPM empirical retrieval models in Dongting Lake, China. The 95 CSPM measurements on 31 August 2012 and 14 June 2013 and their corresponding MODIS Terra images were used to calibrate models, and the model calibration results showed that the 250 m MODIS red band obtained better fitting accuracies than the near infrared band; the quadratic and exponential models of single red band explained 75% (estimated standard errors (SE) = 6.19 mg/l) and 71% (SE = 6.54 mg/l) of the variation of CSPM; and the quadratic and exponential models of red minus shortwave infrared (SWIR) band at 1240 and 1640 nm explained 72–73% (SE = 6.43–6.48 mg/l) and 68–69% (SE = 6.83–6.96 mg/l) of the variations of CSPM, respectively. The quadratic and exponential models of red band and red minus SWIR band were applied to the MODIS Terra image on 16 September 2013 to estimate CSPM values. By comparing the estimated CSPM values on 16 September 2013 and the measured ones on 17 September 2013 at 40 sampling points for model validations, the results indicated that there exited significantly strong correlations between the measured and estimated CSPM values at a significance level of 0.05 for all models, and the exponential model of red minus SWIR band at 1240 nm achieved the best estimation result within all models. Such result provided foundation for obtaining the spatiotemporal distribution information of CSPM from MODIS images in Dongting Lake, which will be helpful for understanding, managing and protecting this ecosystem.