In this research, different techniques for the estimation of Bond grindability (Gbg ) values of coals are studied. Data from ten sub-bituminous coals from Turkey are used by featuring physicomechanical (ISI, Is, and FD ) and eight chemical coal parameters, which include proximate analysis (moisture, ash, volatile matter, fixed carbon, and calorie). Linear and multivariable linear regression techniques are used for predicting the Gbg values for the specified coal parameters. Results indicate that a multivariable linear regression gave the most accurate Gbg prediction than simple regression in the estimation process.