Medical ultrasound images are inherently corrupted with speckle noise. The knowledge of the statistics of the speckle is necessary for developing effective methods to reduce speckle noise. In this paper, the Bessel K-Form (BKF) probability density function (PDF) is proposed to model the logarithmically transformed speckle noise. A maximum likelihood -based method is developed for estimating the BKF parameters. The appropriateness of the BKF distribution in modeling the speckle is studied for different noise levels in the wavelet and curvelet transform domains. It is shown that the BKF can capture the noise statistics better than the Gaussian and normal inverse Gaussian PDFs.