Nothing more to explain. I just don't know how to find the best fitting plane given a set of N points in a 3D space. I then have to write the corresponding algorithm. Thank you ;)
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Subtract out the centroid, form a $3\times N$ matrix $\mathbf X$ out of the resulting coordinates and calculate its singular value decomposition. The normal vector of the best-fitting plane is the left singular vector corresponding to the least singular value. See this answer for an explanation why this is numerically preferable to calculating the eigenvector of $\mathbf X\mathbf X^\top$ corresponding to the least eigenvalue.