  In this paper, we derive new probability bounds for Chebyshev's inequality if
the supremum of the probability density function is known. This result holds
for one-dimensional or multivariate continuous probability distributions with
finite mean and variance (covariance matrix). We also show that the similar
result holds for specific discrete probability distributions.
