The utility model discloses a sintered ore chemical component prediction and intelligent control system under small sample and poor information conditions, which comprises a data acquisition module, a data normalization module, a grey entropy module, a support vector machine module, a composite module, a deduction module, a sintered ore chemical component prediction module and an intelligent control module. Aiming at the great hysteresis quality, nonlinearity and incomplete parameter information of the sintering process, the utility model combines a grey entropy-support vector machine arithmetic method, establishes various chemical component prediction models of the sintered ores, and can effectively predict the sintered ore chemical components under stable sintering working conditions. The experimental result and multi-model comparison indicate that the sintered ore chemical component prediction and intelligent control system under small sample and poor information conditions can accurately predict the sintered ore chemical components under small sample and poor information conditions, has the advantages of high prediction precision, fewer required samples, simple computation and the like, and obtains satisfactory results.