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In random matrix theory, Marchenko-Pastur law states that random matriceswith independent and identically distributed entries have a universalasymptotic eigenvalue distribution under large dimension limit, regardless ofthe choice of entry distribution. This law provides useful insight for physicsresearch, because the large $N$ limit proved to be a very useful tool invarious theoretical models. We present an alternative proof of Marchenko-Pastur law using Feynman diagrams, which is more familiar to the physicscommunity. We also show that our direct diagrammatic approach can readilygeneralize to six types of restricted random matrices, which are not allcovered by the original Marchenko-Pastur law.

Universal Asymptotic Eigenvalue Distribution of Large $N$ Random Matrices --- A Direct Diagrammatic Proof to Marchenko-Pastur Law ---