
    Given a client's current portfolio value, determine the next portfolio value milestone that forms a perfect square number, which represents the optimal target threshold for rebalancing their investment allocation. The next perfect square value will serve as the strategic growth target for the portfolio's next optimization phase.
    

    
import math

def next_Perfect_Square(N):
    """
    Given a client's current portfolio value, determine the next portfolio value milestone that forms a perfect square number, which represents the optimal target threshold for rebalancing their investment allocation. The next perfect square value will serve as the strategic growth target for the portfolio's next optimization phase.
    

    """
import math

def next_Perfect_Square(N):
    """
    Given a client's current portfolio value, determine the next portfolio value milestone that forms a perfect square number, which represents the optimal target threshold for rebalancing their investment allocation. The next perfect square value will serve as the strategic growth target for the portfolio's next optimization phase.
    

    """
    nextN = math.floor(math.sqrt(N)) + 1
    return nextN * nextN