Disclosed are a method of predicting mature microRNA regions using a bidirectional hidden Markov model and a medium recording a computer program to implement the method. The method includes representing each base pair comprising the microRNA precursor by state information of match, mismatch and bulge states; representing the base pair by a basepair emission symbol; computing a Viterbi probability (P) for microRNA using a probability (E.sub.s(q)) that state s emits symbol q and a transition probability (T.sub.ab) from state a to state b; computing a Viterbi probability (P.sub.t(i)) that the i-th base pair is true and another Viterbi probability (P.sub.f(i)) that the i-th base pair is false; and computing a position probability (S(i)) for mature microRNA using the Viterbi probability, wherein, if the position probability (S(i)) for mature microRNA is greater than a predetermined value, the position at which the base pair is present is taken as the mature microRNA region. The method of predicting a mature microRNA region makes it possible to perform learning and searching for a shorter period of time and has high prediction efficiency. Also, the method is capable of identifying microRNA genes and predicting mature microRNA regions at the same time. Thus, the present invention has a beneficial effect of supplying a much larger amount of information.