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In this paper we present a new iteration-complexity bound for the Mizuno--Todd--Ye predictor-corrector (MTY P-C) primal-dual interior-point algorithm for linear programming. The analysis of the paper is based on the important notion of crossover events introduced by Vavasis and Ye. For a standard form linear program min {cTχ: Aχ = b, &chi ≥ 0 } with decision variable ..., we show that the MTY P-C algorithm, started from a well-centered interior-feasible solution with duality gap nμ0 finds an interior-feasible solution with duality gap less than nn in O (T(μ0/η)+n3.5 log (Χ*A)) iterations, where T(t ) =min {n² log (log t), log t} for all t>0 and Χ*A is a scaling invariant condition number associated with the matrix A. More specifically,Χ*A is the infimum of all the conditions numbers XAD, where D varies over the set of positive diagonal matrices. Under the setting of the Turing machine model, our analysis yields an O (n3.5 LA + min {n² log L, L}) iteration-complexity bound for the MTY P-C algorithm to find a primal-dual optimal solution, where LA and L are the input sizes of the matrix A and the data (A,b,c ), respectively. This contrasts well with the classical iteration-complexity bound for the MTY P-C algorithm, which depends linearly on L instead of log L. [ABSTRACT FROM AUTHOR]