LDPC code recognition is a difficult issue in channel coding recognition. With the widespread application of LDPC code in communication field, LDPC code recognition technology has been attracted more and more attention. Aiming at the problem that the existing methods have been suffering weak identification performance in low SNR environment, a LDPC coding method with maximum mean square ratio is proposed in this paper. Firstly, the coded verification relation is mapped to the log-likelihood ratio domain using the soft information output in the channel, and the parity check log-likelihood ratio (CLLR) is defined. Then, the modulus statistical properties of CLLR are analyzed, and the relationship between CLLR and the parameters of LDPC code is established. Finally, using the difference of statistical properties of CLLR under different check matriices, a method of maximum mean and variance ratio based decision device is proposed. The simulation results show that the proposed algorithm is superior to the existing algorithms in the finite set application model, and the recognition gain can reach 2 dB to 5 dB in the low SNR environment. Moreover, for the recognition of high bit rate LDPC codes, the algorithm can significantly improve the recognition performance.