find the best fit distribution that fits the data

how could I find the best probability distribution that fits a failure rate data?

I try:

 val=[0;1;2;3;4;5;6;7;8;9;10;11;12;13;14;15;16;17;18;];   % time
n=[4;7;9;7;14;12;18;29;25;30;39;40;33;46;46;59;62;60;62;]  % failure rate

Exponential distribution

ex=expfit(n);            % n estimate parameters maximum likelihood exponential 
Ee=exppdf(n,ex);     % exponential pdf
figure
plot(val,n/trapz(val,n),'ro');hold on   %resize/scaling the data 
plot(val,Ee,'-g')

Poisson distribution

[l,lci]=poissfit(n);          % n  estimate parameters maximum likelihood poisson
p=poisspdf(n,l);     % poisson pdf
stem(val,p,'k-')

Normal distribution

pd = fitdist(n,'Normal')       
ynormal = pdf(pd,n);
plot(val,ynormal,'m-','LineWidth',2)
axis([-1 19 0 0.12]);
grid on
AAY=legend('data','Exponential','poisson','normal'); %

which produce this figure:

NO BEST FIT in the figure.

How I can modify the code to find the best fit distribution?