In　video　coding,　although　inter-channel　redundancy　has　been　somewhat　decorrelated　through　the　conversion　of　RGB-to-YUV,　there　are　still　some　correlations　among　Y,　Cb,　and　Cr　components　[1].　As　a　result,　chroma　components　can　be　predicted　from　the　luma　component　based　on　a　linear　model.　The　parameters　of　the　linear　model　are　estimated　through　a　Least　Square　Solution　(LSE)　by　using　reconstructed　neighboring　chroma　and　the　causal　luma　samples　as　training　data　at　both　the　encoder　and　the　decoder　sides.　However,　it　is　difficult　to　derive　the　optimal　parameters　especially　when　there　are　insufficient　training　samples　for　prediction　blocks　with　smaller　sizes.　To　address　this　issue,　we　propose　new　method　on　deriving　linear　model　and　multi-model　linear　model　based　on　up-sampling　chroma　samples　(LM_UP　and　MMLM_UP)　for　chroma　intra　prediction.　This　proposed　method　performs　consistently　better　than　the　state-of-the-art　Joint　Exploration　Model　version　7　(JEM-7.0)　with　an　average　of　0.06%,　0.31%,　and　0.25%　BD-rate　reduction　for　Y,　Cb,　and　Cr　components,　respectively,　while　the　complexity　increases　at　both　encoder　and　decoder　sides　are　negligible.