Manipulating tensor shapes in TensorFlow.js involves reshaping, transposing, slicing, and concatenating tensors to meet specific input requirements for neural networks. Functions like tf.transpose and tensor.cast enable dimension permutations and type conversions, essential for advanced deep learning workflows. Understanding these operations is crucial for efficient model construction.