The uniaxial compressive strength (UCS) of rock is an important parameter required for design and analysis of rock structures, and rock mass classification. Uniaxial compression test is the direct method to obtain the UCS values. However, these tests are generally tedious, time-consuming, expensive, and sometimes impossible to perform due to difficult rock conditions. Therefore, several empirical equations have been developed to estimate the UCS from results of index and physical tests of rock. Nevertheless, numerous empirical models available in the literature often make it difficult for mining engineers to decide which empirical equation provides the most reliable estimate of UCS. This study evaluates estimation of UCS of rocks from several empirical equations. The study uses data of point load strength (Is(50)), Schmidt rebound hardness (SRH), block punch index (BPI), effective porosity (n) and density (ρ) as inputs to empirically estimate the UCS. The estimated UCS values from empirical equations are compared with experimentally obtained or measured UCS values, using statistical analyses. It shows that the reliability of UCS estimated from empirical equations depends on the quality of data used to develop the equations, type of input data used in the equations, and the quality of input data from index or physical tests. The results show that the point load strength (Is(50)) is the most reliable index for estimating UCS among the five types of tests evaluated. Because of type-specific nature of rock, restricting the use of empirical equations to the similar rock types for which they are developed is one of the measures to ensure satisfactory prediction performance of empirical equations. Keywords: Uniaxial compressive strength (UCS), Empirical equation, Index test, Physical test, Uniaxial compression test, Statistical analysis